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3. 3 3 Analyzing HST Images This section describes methods for using STSDAS and IRAF to work with two dimensional image data from HST Subjects include e Relating your image to sky coordinates e Examining and manipulating your image e Working with STIS ACS and NICMOS imsets e Converting counts to fluxes INTRO 3 10 Chapter 3 STSDAS Basics 3 3 1 Basic Astrometry This section describes how to determine the orientation of an HST image and the RA and Dec of any pixel or source within it including e Tasks that supply positional information about HST images e Met
4. 0 cceceeeeeeeeeees 5 5 5 3 Photometric Calibrations ccccceeeeteeeeee 5 6 5 3 1 Units for NICMOS Photometry 5 6 5 3 2 Fluxes and Magnitude Zeropoints eee 5 6 5 3 3 Photometric Corrections ccccccccccceeeeeeeeeeeeeeees 5 12 5 3 4 Absolute Photometry for Emission Line Filters ci icurrspteincactenannsiesiatheetion ite 5 17 5 3 5 Absolute Spectrophotometry with NICMOS Gris iS iirccrvecsveecs tend idseatateiaceesheceeenet 5 18 5 4 Astrometry Pixel scales and Geometric Distortion cece cseeeeeeeeeeteceeeseeeees 5 19 5 4 1 Pixel Scale Time Dependence cceee 5 19 5 4 2 X and Y Pixel Scale Differences 066 5 20 5 4 3 Geometric Distortion ccccccccccscecceeeeeeeeeeeeeeeeees 5 20 DAA DUZZAING se aaeeea a 5 22 5 4 5 Absolute Astrometry 0 ccccceeeeeeeeeeeeeeeeeeeeees 5 22 5 5 PSF Subtraction ccccccscsscsssccsecsscsssesssssensensteseeee 5 23 5 5 1 Impact of Instrumental Effects on PSE SUD UACHOMN sis sesinin inii aeneis 5 25 5 6 Coronagraphic Reductions ccccccceeeeeeees 5 29 5 6 1 Data Products and File Structures 000 5 29 5 6 2 Coronagraphic ACQuiSitiONS cccceeeeeeeeeeees 5 29 5 6 3 Positions of the Hole and Target 5 32 5 6 4 Recalibrating Coronagraphic Images 0 5 35 5 6 5 Reducing and Co adding Coronagraphic IMageS cecccccccccccceeeeeeeeeeeeeeeeeees 5
5. cl gt splot yOcy0108t clh 8 save_file results log If you have used tomultispec to transform a STIS echelle spectrum into imh pix OIF files with WCS wavelength information see tomultispec on page 3 27 you can step through the spectral orders stored in image lines using the and keys To start with the first entry in your OIF file type cl gt splot new_ms imh 1 You can then switch to any order for analysis using the key to increment the line number the key to decrement and the key to switch to a specified image line Note the beam label that gives the spectral order cannot be used for navigation See the online help for details Analyzing HST Spectra J INTRO 3 33 Table 3 6 Useful splot Cursor Commands Command Purpose Manipulating spectra f Arithmetic mode add and subtract spectra l Convert spectrum from f to f invert transformation with n n Convert spectrum from f to fy s Smooth with a boxcar u Define linear wavelength scale using two cursor markings Fitting spectra d Mark two continuum points amp de blend multiple Gaussian line profiles e Measure equivalent width by marking points around target line h Measure equivalent width assuming Gaussian profile k Mark two continuum points and fit a single Gaussian line profile m Compute the mean RMS and S N over marked region t Enter interactive curve fit function usually used f
6. C 1 Observation Log Files C 1 C 2 Retrieving Observation Logs C 9 C 3 Using Observation Logs C 10 This Appendix describes the Observation Log Files also known as OMS or jitter files These files record pointing jitter and other Pointing Control System PCS data taken during an HST observation You can use them to assess the behavior of the HST spacecraft during your observation and in particular to evaluate the jitter of the spacecraft while it was taking data Here we describe the contents and structure of the observation log files how to retrieve them from the Archive and how to work with the data they contain C 1 Observation Log Files Observation log files associated with each HST dataset contain pointing and specialized engineering data taken during the observation These data files are produced by the Observatory Monitoring System OMS an automated software system that interrogates the HST engineering telemetry and correlates the time tagged engineering stream with HST s Science Mission Schedule SMS the seven day command and event list that drives all spacecraft activities This system reports the status of the instruments and observatory and flags discrepancies between planned and executed actions OMS provides observers with information about guide star acquisition pointing and tracking that is not normally provided in the science headers APP C 1 APP C 2 Appendix C Observation Log Files The observ
7. Enter the type of terminal or workstation you will most often use with IRAF Generic terminal types that will work for most users are e vt100 for most terminals e xtermjhs for most workstations running under X Windows xgterm for sites that have installed X11 IRAF and IRAF v2 10 3 BETA or later You can change your terminal type at any time by typing set term new_type during an IRAF session You can also change your default type by editing the appropriate line in your login cl file After you enter your terminal type you will see the following output before getting your regular prompt A new LOGIN CL file has been created in the current You may wish to review and edit this file to change The login cl file is the startup file used by the IRAF command language CL It is similar to the LOGIN COM file used by VMS or the login file used by Unix Whenever IRAF starts it looks at the login cl file You can edit this file to customize your IRAF environment In fact you should look at it to make sure that everything in it is correct In particular there is a line starting with set home that tells IRAF where to find your IRAF home directory You should verify that this statement does in fact point to your IRAF directory If you will be working with standard IRAF format images you should also insert a line saying set imdir HDRS The imdir setting is ignored when working with GEIS format images T
8. cl gt imcopy fitsfile fits sci 2 noinherit gt gt gt outfile fits sci 2 overwrite Working with FITS Table Extensions STIS and NICMOS use FITS tables in two basic ways Both instruments produce association tables see appendix B 3 listing the exposures that go into constructing a given association product In addition STIS provides certain spectra calibration reference files and time tagged data in tabular form Here we describe e How to access and read FITS table extensions e How to specify data arrays in FITS table cells This discussion assumes you are using STSDAS 2 0 or later The IRAF FITS kernel deals only with FITS images The tables package installed with STSDAS handles FITS table extensions Accessing FITS Tables You can access data in FITS table extensions using the same tasks appropriate for any other STSDAS table and the syntax for accessing a specific FITS table is similar to the syntax for accessing FITS images see section 2 2 1 with the following exceptions INTRO 2 10 Chapter 2 HST File Formats e The FITS table interface does not support header keyword inherit ance e FITS tables cannot reside in the primary HDU of a FITS file They must reside instead in a FITS table extension in either ASCII form XTENSION TABLE or binary form XTENSION BINTABLE e Ifthe first extension in a FITS file is a TABLE or a BINTABLE you can access it by typing the file name with no extension specified
9. Horne K 1988 in New Directions in Spectrophotometry A G D Philip D S Hayes and S J Adelman eds L Davis Press Schenectady NY p 145 e Koorneef J R Bohlin R Buser K Horne and D Turnshek 1986 in Highlights of Astronomy Vol 7 J P Swinds ed Reidel Dor drecht p 833 Kriss G 1994 in Astronomical Data Analysis Software and Systems IIT PASP Conference Series Vol 61 p 437 PART Il NICMOS Data Handbook This handbook is designed to help you manipulate process and analyze data from the Near Infrared Camera and MultiObject Spectrograph NICMOS on board the Hubble Space Telescope HST Hi Part IIl NICMOS Data Handbook ntroduction How to Use this Handbook This handbook is designed to help you manipulate process and analyze data from the Near Infrared Camera and MultiObject Spectrograph NICMOS on board the Hubble Space Telescope HST This is presented as an independent and self contained document extensively built on the contents of an older edition version 3 0 of the HST Data Handbook The old HST Data Handbook has now been subdivided into separate volumes for each instrument Users who wish to find more general information about details of acquiring HST data from archive their file formats and general purpose software for displaying and processing these data are referred to a companion volume the Introduction to the HST Data Handbook The current edition of the NICMOS D
10. Most tasks in IRAF and STSDAS operate on files and expect you to specify a file name for one or more parameters Several types of special syntax can be used with certain tasks when specifying file names These syntax features include e Wild card characters often called templates which are used to specify multiple files using pattern matching techniques The wild cards are Matches any number of characters e g z2 cOh Matches any single character e g 201x23x c h 3 The binary data file format is host dependent and may require translation before it can be moved to a computer using a different architecture APP A 14 Appendix A IRAF Basics 17 ie Pl 2 When using wildcards with image processing tasks be sure to exclude the binary pixel files by ending your file name specification with an h for example y h e List files often called files which are ASCII file that contain lists of file names one per line If your task supports the list file feature you would type the name of your list file preceded by the char acter For example files txt Image section specification Tasks that work with image data will often let you specify that you want to work on only a small area of the image rather than the entire image To extract a particular image section specify each axis range in square brackets for example image hhh 10 200 20 200 IRAF networking specification IRAF is c
11. NSAMP and EXPTIMEB and then for each imset of the multiextension fits file it lists the corresponding SAMPNUM SAMPTIME and DELTATIME values These can be useful bits of information when using non standard processing techniques such as the biaseq routine An example of the use of sampinfo and its output is given in section 4 1 5 nicpipe biaseq pedsky and pedsub The nicpipe task provides a shortcut for partially processing NICMOS images through some but not all stages of calnica Normally this is meant for use in preparing images for bias equalization using the biaseq task see chapter 4 Setting stage biaseg takes the processing through the steps ZSIGCORR ZOFFCORR MASKCORR BIASCORR NOISCALC DARKCORR NLINCORR and BARSCORR Setting stage final completes the processing This can also be done by hand using chealpar or hedit to change the processing control switches in the image headers see section 3 5 2 and running calnica directly Occasionally nicpipe can come in handy at other times besides biaseq processing one example is given below NICMOS 5 4 Chapter 5 Data Analysis The tasks biaseq pedsky and pedsub provide methods for dealing with the floating quadrant bias or pedestal effect in some not all data sets and are described in section 4 1 5 sampdiff and sampcum The sampdiff task provides a convenient way to convert a MULTIACCUM image into a set of independent first differences Normally e
12. OPS py AP ed pepe pe eh A 0 250 500 750 1000 1250 Sample Time sec The upturn in the counts during the last few readouts indicates the presence of scattered light at the end of the exposure It is sometimes easier to see the effects of scattered light if you look at the first differences in an image i e the difference between each readout and the preceding one In that way you see only the counts that were accumulated during that readout sample and not the cumulative sum of everything that came before This can be done using the task sampdiff in the nicmos package again see chapter 5 ni gt sampdiff n4uxllufq_ima fits n4uxllufq_fdiff fits ni gt pstats n4uxllufq fdiff fits gt gt gt extname sci units counts stat midpt Figure 4 13 Median counts per IMSET for the first difference image computed from the _ima fits file using sampdiff The upturn due to scattered light is more prominent when viewed this way u Fri 18 20 15 15 0ct 1 NOAO IRAF V2 11 2EXPORT med bathshe n4uxilufq_fdiff ee S FA ABA AE SAE BS i S SAE SE Counts DN a T INEEN EE TS Leake ae aD E L AS AA GE AE ER 1 TENi AA AAEN ri 1 0 250 500 750 1000 1250 Sample Time sec The easiest and safest way to eliminate the effects of scattered light is to discard the affected readouts before fitting with CRIDCALC to compute the count rates and identify the cosmic rays This will cost you part of the Scattered Earthli
13. People Yellow Pages 8 Download gf Calendar C4 Channels HST Archive Search Archive Status Important Downtime Message Gl What s Related Other Mission Search Pages SIMBAD NED Don t resolve Resolve _GHRS _NICMOS FOC Observation Band Central wavelength falls in this range A A Output cohonns aDefault Custom J2000 _ Show SQL query Reading HST Data Tapes and Disks IJ INTRO 1 21 This command will make GEIS format copies having extension hhh of all the FITS files in the directory with the same rootname Following reduction and analysis of the GEIS files with the IRAF STSDAS tasks they may be written back into FITS format on hard disk or to a tape or other storage media with the stwfits task INTRO 1 22 Chapter 1 Getting HST Data CHAPTER 2 HST File Formats In this chapter 2 1 Historical Perspective 2 2 2 2 FITS File Format 2 3 2 3 GEIS File Format 2 12 STScI automatically processes and calibrates all the data received from HST The suite of software programs that performs this processing part of a system known as OPUS is frequently called the pipeline and its purpose is to provide data to observers and to the HST Data Archive in a form suitable for most scientific analyses Pipeline processing assembles data received from HST into datasets calibrates the data according to standard procedures des
14. The residual bias or pedestal effect was described in section 4 1 2 and should be removed if possible before analyzing coronagraphic data The pedsky task described in section 4 1 5 may not be suitable for coronagraphic images where a bright object dominates the field of view In this case the pedsub task may be more appropriate This method has been used successfully with coronagraphic images from the SMOV calibration program 7052 1997 July 23 The pedsub task was run with the parameters filter mask i e applies unsharp masking filter to remove low spatial frequency information and doquadeq no i e do not force quandrant boundaries to be continuous The images of the stellar PSF in the coronagraphic images of the 7052 data fill the quadrant with the coronagraphic hole and spill over into adjacent quadrants This constrains the determination of the pedestal contribution in that quadrant A mask file was created to flag bright pixels threshold limit 4 0 cts sec the flagged pixels were not used for estimating the pedestal contribution This mask was added to the mask of known bad pixels included in the DQ image extension and the pedsub parameters dqon and dqpar were used to tell the task which mask values correspond to pixels that should be ignored when fitting the pedestal Removing Other Image Artifacts The identification and removal of bad pixels grot and other NICMOS data anomalies are discussed in chapter 4 For coron
15. Title title wildtext PI Last name pi_lastname varchar ay straact n wildtext EG IDeje725 id Cycle eb Tac Pane AES PI Last name Zep Tite vye propose to study the formation history of elliptical lt galaxies by obtaining far UY photometry of their globular clusters The far U photometry will be used in conjunction with existing optical data to constrain the ages of these clusters and thus the formation One record matched search criteria Snap Table _ No Update L L OULNI W mones ym eq Bum Figure 1 5 Example of Cross Correlation Feature in which Target Name has been chosen as the common feature to search for in two Quick Search result lists StarView Cross Qualification Query Results from Mapped to Query in Results for Quick Search v Results for Quick Search 2 v Available Fields Selected Fields Selected Fields Available Fields Target Name View Fieldsas Target Name Dataset Name Labels F RA Dec Instrument Flag C Apertures Be Central Vwavelen i z a Proposal ID Central Vwavelent Proposal ID Release Date PI last name Target Name Target Descriptic Config ao PE Cancel ed LSH Buijed Joideyo W vi l OULNI 1 2 6 1 2 7 Getting Data with StarView HJ INTRO 1 15 StarView and the Visual Target Tuner The Visual Target Tuner VTT is part of the Astronomer s Propos
16. Version 5 0 January 2002 HST Data Handbook for NICMOS Hubble Division 3700 San Martin Drive Baltimore Maryland 21218 help stsci edu Operated by the Association of Universities for Research in Astronomy Inc for the National Aeronautics and Space Administration User Support For prompt answers to any question please contact the STScI Help Desk e E mail help stsci edu e Phone 410 338 1082 800 544 8125 U S toll free World Wide Web Information and other resources are available on the Web site e URL http www stsci edu NICMOS Revision History Version Date Editors 1 0 February 1994 Stefi Baum 2 0 December 1995 Claus Leitherer 3 0 Vol I October 1997 Mark Voit 3 0 Vol II October 1997 Tony Keyes 3 1 March 1998 Tony Keyes 4 0 December 1999 Mark Dickinson 5 0 January 2002 Bahram Mobasher Chief Editor HST Data Handbook Michael Corbin Jin chung Hsu Editors HST Introduction Mark Dickinson Editor NICMOS Data Handbook Contributors M Dickinson S Arribas L E Bergeron T Boeker D Calzetti S T Holfeltz B Mobasher B Monroe K Noll E Roye A Schultz M Sosey C Xu Citation In publications refer to this document as Dickinson M E et al 2002 in HST NICMOS Data Handbook v 5 0 ed B Mobasher Baltimore STScI Send comments or corrections to Hubble Division Space Telescope Science Institute 3700 San Martin Drive Baltimore Maryland 21218 E m
17. implot magnify msarith mscombine msstatistics newcont pixcoord plcreate rotate saodump siaper images imfilter stsdas toolbox imgtools stsdas toolbox imgtools images immatch images immatch stsdas graphics stplot stsdas toolbox imgtools stsdas toolbox imgtools images tv images tv plot images imgeom stsdas toolbox mstools stsdas toolbox mstools stsdas toolbox mstools stsdas graphics stplot stsdas hst_calib wfpc xray ximages images imgeom stsdas graphics sdisplay stsdas graphics stplot Boxcar smooth a list of images Combine images using various algorithms and rejection schemes Copy GEIS multigroup images Compute a coordinate transformation Resample an image based on geomap output List of file names of all groups of a GEIS image to make lists Compute image statistics Perform general arithmetic on GEIS images Fill in regions of an image by interpolation Examine images using display plots and text see imexamine on page 3 13 Plot lines and columns of images see implot on page 3 12 Magnify an image Performs basic arithmetic on STIS and NICMOS imsets Extension of gcombine for STIS and NICMOS imsets Extension of gstatistics for STIS and NICMOS imsets Draw contours of two dimensional data Compute pixel coordinates of stars in a GEIS image Create a pixel list from a region file e g from SAOimage Rotate an image Make image and colormap files from SAOimage display Plot sc
18. nref i711653gn_lin fits detector nonlinearities file DARKFILE nref had12036n_drk fits dark current file FLATFILE nref hbi1346en_flt fits flat field file PHOTTAB ntab i711229 n_pht fits photometric calibration table BACKTAB N A 7 background model parameters table CALNICA CALIBRATION REFERENCE FILE PEDIGREE MASKPDGR INFLIGHT 15 07 1998 static data quality file pedigree NOISPDGR GROUND 27 01 1997 detector read noise file pedigree NLINPDGR GROUND 7 detector nonlinearities file pedigree DARKPDGR MODEL 11 10 1997 dark current file pedigree FLATPDGR INFLIGHT 13 11 1997 flat field file pedigree PHOTPDGR INFLIGHT 05 08 1997 07 08 1997 photometric calibration table ped BACKPDGR background model parameters table pedigree CALNICA CALIBRATION SWITCHES perform omit BIASCORR PERFORM subtract ADC bias level ZSIGCORR PERFORM Zero read signal correction ZOFFCORR PERFORM subtract MULTI ACCUM zero read MASKCORR PERFORM data quality initialization NOISCALC PERFORM calculate statistic errors NLINCORR PERFORM correct for detector nonlinearities DARKCORR PERFORM dark correction BARSCORR PERFORM bars correction FLATCORR OMIT 7 flat field correction UNITCORR OMIT 7 convert to count rates PHOTCALC PERFORM calculate photometric keywords CRIDCALC PERF
19. presents a two dimensional histogram of the point ing fluctuations during the observation You can display it to visualize the spacecraft stability during you observation and is information for deconvolutions and PSF analyses e rootnamej jit This table the analog to the cmi table contains data that were averaged over three second intervals Its content is identical see table C 3 e rootnamej_jif fits FITS file that is actually the de archived product This file can be converted to the jih jid GEIS file via the strftis routine e rootnamej_jit fits The de archived FITS file corresponding to the jit IRAF table It can be converted via strfits C 1 2 Observation Log File Contents February 1997 version The contents of observation log files created since February 1997 are as follows e rootnamej_jif fits The de archived FITS file Unlike the pre vious OMS epoch this FITS file does not bundle a GEIS file and can not be converted with strfits This was done to more closely correlate the observation log files with the STIS and NICMOS FITS files with extensions and associations OMS will normally put all associated observation logs into a single file to correspond to the associated sci ence exposures However if even one science exposure is orphaned not associated then an individual observation log FITS file will be produced for every exposure in that association For a description of STIS and NICMOS association files see a
20. 2 5 log PHOTFNU x CR x F Vega where ZP Vega is the magnitude of Vega Under the CIT infrared photometry scale Vega is defined to have ZP Vega 0 0 whereas in the Arizona system e g Campins et al 1985 AJ 90 896 Vega has ZP Vega 0 02 NICMOS 5 10 Chapter 5 Data Analysis Table 5 1 NIC1 Photometric Zeropoints Spectral Element Spent On D LNT ae FO90M 4 883E 18 1 332E 05 2156 1 FO9SN 7 397E 17 2 244E 04 1733 7 FO97N 5 847E 17 1 841E 04 2217 8 F108N 3 994E 17 1 559E 04 1881 0 F110M 1 743E 18 7 068E 06 1820 7 F110W 5 545E 19 2 358E 06 1773 7 F113N 2 967E 17 1 263E 04 1768 0 F140W 2 027E 19 1 402E 06 1304 7 F145M 8 066E 19 5 702E 06 1195 8 F160W 2 901E 19 2 499E 06 1039 3 F164N 6 161E 18 5 567E 05 965 4 F165M 5 497E 19 4 985E 06 985 1 F166N 6 087E 18 5 600E 05 1010 0 F170M 4 766E 19 4 631E 06 945 4 F187N 4 265E 18 5 000E 05 7729 F190N 4 127E 18 4 962E 05 805 5 POLOS 1 866E 18 6 996E 06 1896 1 POL120S 1 843E 18 6 912E 06 1896 1 POLS240S 1 844E 18 6 914E 06 1896 1 These values have not been recalibrated and are taken from PHOTTAB 17112297n_pht fits Photometric Calibrations W NICMOS 5 11 Table 5 2 NIC2 Photometric Zeropoints Spectral Element PHOTFLAM PHOTFNU F Vega erg cm A DN Jy sec DNH Jy F110W 4 382E 19 1 861E 06 1775 0 F160W 2 401E 19 2 066E 06 1040 7 F165M 4 541B 19 4 132E 06 982 8 F171M 1 061E 18 1 048E 05 930 7 F180M 1 012E 18 1 09
21. 5 725897 0 0905327 Feature 1 FWHM var coeff6 1 516265E 14 2 740680E 16 Feature 2 amplitude var coeff7 4963 262 0 06048062 Feature 2 center var coeff8 6 448922 0 116878 Feature 2 FWHM var coeff9 4 350271E 14 2 903318E 16 Feature 3 amplitude var coeff10 5011 731 0 01856957 Feature 3 center var coeff11 6 415922 0 03769293 Feature 3 FWHM var rms 5 837914E 16 grow 0 naverage 1 low_reject 0 high_reject 0 niterate 1 sample 4800 132 5061 308 References W INTRO 3 37 3 5 5 specfit The specfit task in the STSDAS contrib package is another powerful interactive facility for fitting a wide variety of emission line absorption line and continuum models to a spectrum This task was written by Gerard Kriss Extensive online help is available to guide you through the task although because it is a contributed task little to no support is provided by the STSDAS group The input spectrum to specfit can be either an IRAF image file or an ASCII file with a simple three column wavelength flux and error format If the input file is an IRAF image the wavelength scale is set using values of WO and WPC or CRVALI and CDELT1 Hence for image input the spectral data must be on a linear wavelength scale In order to retain data on a non linear wavelength scale it is necessary to provide the input spectrum in an ASCII file so that you can explicitly specify the wavel
22. A type 51 slew is used to track moving targets planets satellites asteroids and comets Observations are scheduled with FINE LOCK acquisition i e with two or one guide stars Usually a guide star pair will stay within the pickle during the entire observation set but if two guide stars are not available a single guide star may be used assuming the drift is small or the proposer says that the roll is not important for that particular observing program An option during scheduling is to drop from FGS control to GYRO control when the guide stars move out of the FGS Also guide star handoffs which are not a simple dropping of the guide stars to GYRO control will affect the guiding and may be noticeable when the jitter ball is plotted The jitter statistics are accumulated at the start of the observation window Moving targets and spatial scan motion will be seen in the jitter data and image Therefore the OMS header keywords V2_RMS and V3_RMS values the root mean square of the jitter about the V2 and V3 axis can be quite large for moving targets Also a special anomaly keyword SLEWING will be appended to the OMS header stating movement of the telescope during the observation This is expected for observing moving targets The following list of cmh header keywords is an example of expected values while tracking a moving target LINE OF SIGHT JITTER SUMMARY V2_RMS 3 2 V2 Axis RMS milli arcsec V2_P2P 17 3 V2 Axis peak
23. Images of the target and coronagraphic hole were obtained a few orbits in advance of the coronagraphic observations and sent to the ground for analysis RT ANALYSIS The same roll of the spacecraft was used for both the acquisition and science visits Usually the same dominant and subdominant guide stars were used for both the acquisition and science observations However in a few instances this was not the case after the slew was performed the target was found outside of the hole either on the edge of the hole or far from the hole The coronagraphic observer as well as future Archive users are advised to check the OPUS PDQ files for suspect observations The background and flat field observations were usually offset as much as 18 25 arcseconds from the target position to avoid the diffraction spike from the image of an overexposed target crossing the coronagraphic hole and introducing errors in the measured position of the coronagraphic hole OPUS staff assisted the PI in identifying the target centroiding and determining offsets A record of the acquisition was written to the PDQ file Positions of the Hole and Target The location of the target and the slew are saved in the embedded engineering data attached to the science observations These values are recovered from the embedded engineering data and written to keywords NXCENT NYCENT NOFFSETX NOFFSETY in the SPT file The first observation following the NICMOS ACQ will contain the
24. In particular if you wanted to plot the flux versus wavelength in STIS echelle order 80 you could type st gt sgraph stis fits 4 r sporder 80 WAVELENGTH FLUX Remember to include the quotation marks Otherwise sgraph will complain about too many positional arguments Note also that sgraph understands only row selector syntax columns are chosen by name The STIS specific echplot task is particularly useful for browsing STIS echelle spectra It can plot single spectral orders overplot multiple orders on a single plot or plot up to four orders in separate panels on the same page For example to overplot the orders contained in rows two through four and row six on a single page cl gt echplot stis_ xld fits 1 r row 2 4 6 output igi gt gt gt plot_style m Note that the plot_style parameter governs how the spectral orders are plotted The plot_style values s m and p plot one order per page several orders on a single plot and one order per panel respectively The default brightness unit is calibrated FLUX although you can specify other quantities e g NET counts using the flux _col parameter See the online help for details Producing Hardcopy This section shows how to generate hardcopies of plots directly and describes igi the Interactive Graphics Interpreter available in STSDAS Direct Hardcopies To print a quick copy of the displayed plot 1 Type gcur in the command window where your CL p
25. Some of the packages you should investigate are e images This package includes general tasks for copying imcopy moving imrename and deleting imdelete image files These tasks operate on both the header and data portions of the image The package also contains a number of general purpose tasks for opera tions such as rotating and magnifying images e stsdas toolbox imgtools This package contains general tools for working with multigroup GEIS images including tasks for working with masks and general purpose tasks for working with the pixel data such as an interactive pixel editor pixedit Figure 3 1 STSDAS Version 2 3 Package Structure stsdas lt a contrib eene i hst_calib y redshift i vla J graphics stplot sdisplay analysis sobsolete tool focutility focgeom l testdata l y_calib j focphot l ctools j paperprod acs stis synphot nicmos j fos hrs dither y fitting fourier j gasp j isophote restore l statistics nebular j timeseries l z_calib l box y tools headers convfile imgtools ttools Implicitly Loaded OULNI E SVGSLS Sunebiaey INTRO 3 4 Chapter 3 STSDAS Basics e stsdas
26. The reduction and analysis of NICMOS grism data benefit from decisions made by the user and from careful interactive examination and are therefore discussed here rather than in the chapter on pipeline calibration IDL software to extract spectra from NICMOS grism images has been developed at Space Telescope European Coordinating Facility ST ECF Two programs are available NICMOSlook which is interactive and calnicc which is non interactive The interactive program NICMOSlook provides a number of tools called from an IDL GUI widget This program is recommended for most extraction because of its versatility and interactive features The automatic version calnicc is recommended if a quick look extraction of a large number of spectra from different images is desired to identify interesting objects Both software packages together with user documentation can be obtained from the ST ECF NICMOS web site Here we offer only a brief description of grism analysis methodology and refer the user to the documentation provided with the software for details The ST ECF also maintains grism calibration reference files which are included with the software distributions Grism data are treated as regular images by the extraction software see section 5 8 1 with the exception that they are not flatfielded by calnica The flatfield correction for a given pixel depends both on the pixel location x y and on the wavelength of the light which is dispersed o
27. is the value at the i th pixel with associated error 0 the weighted mean and variance used in the task are ee is 7 J 0 X O iis 1 J 0 X O and 1 2r at 0 opi 1 10 X O The data quality information carried by the STIS ACS or NICMOS file is used to reject pixels in the statistical computation Users can supply additional masks to reject objects or regions from the science arrays mssplit and msjoin The mssplit task extracts user specified imsets from a STIS ACS or NICMOS data file and copies them into separate files Each output file contains a single imset along with the primary header of the original file You might find this task useful for reducing the size of a STIS ACS or Analyzing HST Images W INTRO 3 17 NICMOS file containing many imsets or for performing analysis on a specific imset The msjoin task inverts the operation of mssplit it assembles separate imsets into a single data file There are additional tasks in this package for deleting and sorting imsets as well as tasks for addressing a specific image class within an imset 3 3 4 Photometry Included in this section are A list of IRAF STSDAS tasks useful for determining source counts Instructions on how to use header keyword information to convert HST counts to fluxes or magnitudes A brief description of synphot the STSDAS synthetic photometry package IRAF and STSDAS Photometry Tasks The following are some useful IRAF S
28. persistence as described e g in the Drizzling Cookbook Gonzaga et al 1998 STScI ISR WFPC2 98 04 A web based tool for determining the time since SAA passage for any given data set is now available from the STScI NICMOS web pages The tool is also linked to the NICMOS History Tool see section 5 2 It accepts a list of observation times specified as modified Julian dates MJD these can be obtained from the EXPSTART image header keyword and NICMOS 4 34 J Chapter 4 Anomalies and Error Sources 4 6 3 generates a list of the elapsed time and durations of the preceding SAA passages as well as a graphical display showing the observation and SAA times Because the amplitude of cosmic ray persistence in NICMOS images depends strongly on both the time elapsed since SAA passage and on the duration of the passage itself this tool provides a useful way of quickly pre screening your data to see which frames are most likely to be contaminated On rare occasions it may happen that dark exposures were taken after an SAA passage but before science observations These darks can provide a map of the cosmic ray persistence and in principle it is possible to scale and subtract them from the subsequent science exposures in order to minimize the effects of the cosmic ray afterglow This has even been done using short science exposures taken early in the orbit scaled and subtracted after masking out objects from the science images that foll
29. text editors you must maintain their standard 80 character line length The hedit task automatically preserves this line length If you need to add or delete group parameters you can use the STSDAS groupmod task in the stsdas hst_calib ctools package The STSDAS chcalpar task described in more detail in the Calibration chapters for each instrument s data INTRO 2 16 Chapter 2 HST File Formats handbook is useful for updating header keywords containing calibration switches and calibration reference files Always edit headers using tasks like hedit eheader and chcalpar Edit ing headers with a standard text editor may corrupt the files by creat ing incorrect line lengths GEIS Data Files Numerous IRAF STSDAS tasks exist for working with GEIS images see chapter 3 of the HST Introduction Most of these tasks operate on only one image at a time so you usually need to specify which group of a GEIS file is to be processed If you do not specify a group your task will choose the first group by default Specifying a Group To specify a particular group in a GEIS file append the desired group number in square brackets to the file name e g z2bd010ft d0h 10 For example to apply the imarith task to group 10 of a GEIS image type the following always refer to a GEIS file by its header file name i e h even though mathematically you are operating on the data portion cl gt imarith indata hhh 10 77 0 outdata
30. 1 4 intermediate multiaccum science file NICMOS NICMOS 2 2 IPPSSOOOT see files naming conventions IRAF basics APP A 1 described INTRO 3 1 APP A 1 documentation INTRO 3 37 obtaining APP A 15 parameter data type APP A 10 piping APP A 6 psikern PostScript INTRO 3 23 setup APP A 2 spectra analysis INTRO 3 30 tasks available APP A 1 J jitter effect on target lock APP C 13 images from OMS APP C 1 plotting APP C 14 K keywords FITS header INTRO 2 7 NICMOS header NICMOS 2 10 see also header L linearization correction NICMOS NICMOS 3 12 Iparam task viewing parameters APP A 9 magnitude from counts INTRO 3 18 Janskys NICMOS data NICMOS 5 16 markdq task mark data quality flags NICMOS 5 2 math see arithmetic mkiraf command IRAF setup APP A 3 mkmultispec task INTRO 3 25 mode NICMOS readout NICMOS 1 4 mosaic NICMOS NICMOS 3 16 NICMOS constructing NICMOS 3 22 mosaic file NICMOS NICMOS 2 3 moving target acquisition APP C 12 msarith task imset arithmetic INTRO 3 15 mscombine task combine imset INTRO 3 15 msjoin task combine imset INTRO 3 16 mssplit task extract imset INTRO 3 16 msstatistics task imset statitistics INTRO 3 16 mstools package FITS image extenstions INTRO 3 4 image sets NICMOS 5 1 MULTIACCUM mode NICMOS NICMOS 1 5 multiple exposures combining NICMOS NICMOS 3 20 multispec format desc
31. 1 TAPEDROP T possible loss of science data TLM_PROB problem with the engineering telemetry TM GAP 404 60 duration of missing telemetry sec SLEWING T slewing occurred during this observation TAKEDATA F take data flag NOT on throughout observation SIPROBnn problem with specified science instrument 2 END notes 1 GSFAIL appears only once in a single header file The following table lists all current possible values for the GSFAIL keyword GSFAIL DEGRADED guide star acquisition failure IN PROGR guide star acquisition failure SSLEXP guide star acquisition failure SSLEXS guide star acquisition failure NOLOCK guide star acquisition failure SREXCS guide star acquisition failure SREXCS1 guide star acquisition failure SREXCS2 guide star acquisition failure SREXCS3 guide star acquisition failure SREXCP guide star acquisition failure SREXCP1 guide star acquisition failure SREXCP2 guide star acquisition failure SREXCP3 guide star acquisition failure UNKNOWN guide star acquisition failure VEHSAFE guide star acquisition failure 2 The SIPROBnn keywords appear in the header file with nn 01 99 The following table lists all current possible values for the SIPROBnn keyword SIPROBnn DCF_NUM unchanged This observation may not have been taken FOS Safing This observation affected when FOS Safed HRS Safing This observation affected when HR
32. 3 16 Chapter 3 STSDAS Basics imset are read from the header keyword PIXVALUE in the TIME extensions Once gcombine has finished mscombine then reassembles the individual output images into imsets and outputs them as one STIS ACS or NICMOS data file The output images and error maps from gcombine form the SCI and ERR extensions of the output imset The DQ extension will be a combination of the masking operations and the rejection algorithms executed in gcombine For NICMOS the TIME extension will be the sum of the TIME values from the input files minus the rejected values divided on a pixel by pixel basis by the number of valid pixels in the output image The final TIME array will be consistent with the output SCI image average or median of the science data The SAMP extension for NICMOS is built from all the input SAMP values minus the values discarded by masking or rejection msstatistics This tool is an extension of gstatistics in the STSDAS package which is in turn an extension of imstatistics The main novelty is the inclusion of the error and data quality information included with STIS ACS and NICMOS images in computing statistical quantities In addition to the standard statistical quantities min max sum mean standard deviation median mode skewness kurtosis two additional quantities have been added to take advantage of the error information the weighted mean and the weighted variance of the pixel distribution If x
33. 3 4 Task msarith Operations Operation Operand2 SCI ERR DQ TIME SAMP ADD file opl op2 Joi kor OR TI T2 S1 82 SUB file op1 op2 lol24 022 OR Tl S1 MULT file op1 op2 opl x op2 01 0p1 02 0p2 OR TI s1 DIV file op1 op2 op1 op2 61 op1 02 0p2 OR Tl S1 ADD constant opl op2 dol 02 SUB constant op1l op2 Jo o MULT constant opl op2 opl x 62 01 Zoply gt 62 op2 T1 op2 DIV constant opl op2 opl op2 o ol opl Ny o2 op2 T1 op2 In table 3 4 the first operand op1 is always a file and the second operand op2 can be either a constant or a file The ERR arrays of the input files o1 and 02 are added in quadrature If the constant is given with an error 02 the latter is added in quadrature to the input ERR array Note that in table 3 4 the pixels in the SCI images are in counts but msarith can also operate on count rates mscombine This task allows you to run the STSDAS task gcombine on STIS ACS and NICMOS data files It divides each imset into its basic components SCI ERR and DQ plus SAMP and TIME for NICMOS to make them digestible for gcombine The SCI extensions become the inputs proper to the underlying gcombine task and the ERR extensions become the error maps The DQ extensions are first combined with a user specified Boolean mask allowing selective pixel masking and then fed into the data quality maps If scaling by exposure time is requested the exposure times of each INTRO
34. 7N using repeated observations of the primary standard stars through a limited set of filters in each camera There is some evidence for a small drift in the throughout with time amounting to roughly 2 over the lifetime of the instrument This is to be expected as the array quantum efficiency is temperature dependent and the instrument temperature gradually warmed throughout Cycle 7 and 7N At present this photometric drift is no larger than other known uncertainties in the absolute photometric calibration of NICMOS and we do not discuss it further here In the future STScI may provide information for correcting the photometric zeropoints as a function of the observation date This will be announced via the NICMOS WWW pages and the Space Telescope Analysis Newsletter STAN It is important to note however that NICMOS photometric zeropoints will almost certainly be significantly Photometric Calibrations I NICMOS 5 13 different in Cycle 11 and beyond when the instrument is operating at a warmer temperature with the NCS Differential Photometry The photometric values provided in the headers are obtained from measurements of standard stars in the central regions of the detectors Both high frequency pixel to pixel and low frequency large scale structures sensitivity variations are corrected using on orbit flats On orbit differential photometry characterization of NICMOS cameras 1 and 2 indicate that residual large scale deviat
35. IRAF for the first time you need to follow these three steps 1 Create your IRAF root directory 2 Move to that directory and set the necessary environment variables or system logicals and symbols 3 Run mkiraf to create a login cl file and a uparm subdirectory Users generally name their IRAF home directory iraf also referred to as your IRAF root directory and set it up in their account s root directory i e the default directory that you are in when you log in to the system The IRAF home directory doesn t need to be in your account s root directory nor does it need to be called iraf but you should not put it on a scratch disk that is periodically erased If you call your root IRAF directory iraf you can set up IRAF as follows Under Unix mkdir iraf cd iraf in login file source Siraf unix hlib irafuser csh site dependent check with your system staff Can be placed setenv iraf usr stsci iraf lt The directory name is S 3 mkiraf Under VMS CREATE DIR IRAF Can be placed SET DEFAULT IRAF in LOGIN COM gt IRAF file MKIRAF Lt S Appendix A Initiating IRAF W APP A 3 The mkiraf command initializes IRAF by creating a login cl file and a subdirectory called uparm After typing the mkiraf command you will see the following mkiraf creating a new uparm directory Terminal types gterm ttyswtgraphics vt640 Enter terminal type
36. In the meantime readers are advised to consult the NICMOS web pages on the Space Telescope Science Institute web site for the latest information regarding NICMOS performance and calibration Bahram Mobasher Chief Editor HST Data Handbook Mark Dickinson Editor NICMOS Data Handbook CHAPTER 1 Instrument Overview In this chapter 1 1 Instrument Overview 1 1 1 2 Detector Readout Modes 1 4 This chapter presents a brief overview of the Near Infrared Camera and Multi Object Spectrometer NICMOS its capabilities readout modes and data products 1 1 Instrument Overview NICMOS was built by Ball Aerospace Corporation for the University of Arizona under the direction of Rodger I Thompson the Principal Investigator A basic description of the instrument and its on orbit performance through the Servicing Mission Orbital Verification program is provided by Thompson et al 1998 We encourage all NICMOS users to reference this paper and to review the related papers in the special issue of ApJ Letters which describe the Early Release Observations and demonstrate the scientific capabilities of NICMOS Many additional papers have now appeared in the literature which document the use of NICMOS in a wide variety of scientific applications The NJCMOS Instrument Handbook and the NICMOS WWW pages at STScI are also valuable sources of information for the NICMOS user particularly concerning technical details of the instrument as we
37. MULTIACCUM sequence or an ACCUM with multiple initial and final reads Typically the extra signal is about 20 30 DN at the corners of the detector and 2 3 DN at the center for each readout The signal is highly repeatable and exactly 4 1 2 NICMOS Dark Current and Bias IJ NICMOS 4 5 linearly dependent on the number of reads The amplifier glow also depends on the length of time for which the amplifiers are switched on which is slightly shorter for ACCUM mode The amplifier glow is a real signal and is subject to photon statistics so it is a source of noise in NICMOS exposures In the processing pipeline and calibration reference files it is considered to be a component of the dark signal although its physical origin and temporal dependence is quite different than that of the thermal dark current Thanks to the repeatability of the signal images calibrated with the appropriate dark frames same MULTIACCUM sequence or same exposure time for ACCUM images will have the amplifier glow removed For the STScI synthetic dark reference files the amplifier glow is modeled as A x y amp x y x NR where A x y is the cumulative signal due to the glow in a sequence amp x y is the amplifier glow signal per readout a function of the pixel location x y and the amp on time and NR is the total number of readouts of the array since the last reset In the corners of a full 26 readout MULTIACCUM response there will be of order 500 800 DN due
38. PSF color dependence on PSF subtraction in different filters Left panels normalized counts log scale in the central column of TinyTim 8000 K and 3000 K blackbody PSFs thin lines The thick line is the difference between the two Right panels absolute value of counts difference as a percent of counts for the 8000 K PSF gt F110W Cp O J o 2 2 40 J gt oy l E O a q D D NI J ae O z 3 y 20 J O gT E 2 O J o dO 5 idi VE a Sa oe ees Se BAE T i ri I YR O ti O 20 40 60 80 100120 100 12 pixel E FI8 W J F18 7W 0 40 4 oO E O ke O GOE q D D NODE E O E F 3 Pa 205 J O 5 E E 2 O P J o SAE n S 10 5 VANNINA 0 ba Mn Wn O 20 40 60 80 100120 O 20 40 60 80 10012 pixel pixel Coronagraphic Reductions J NICMOS 5 29 5 6 Coronagraphic Reductions 5 6 1 5 6 2 Data Products and File Structures NICMOS coronagraphic observations consist of an acquisition image and science observations The acquisition could be an onboard acquisition performed by the NICMOS flight software FSW during the same visit as the science observations Or a real time acquisition may have been performed by sending the acquisition image s to the ground for analysis by the Observation Support System OSS and Post Observation Data Processing System PODPS Unified System OPUS personnel during the firs
39. Secondary standard red standard 7904 7816 BRI0021 11 1 0 75 0 52 Secondary standard red standard 7904 7816 Absolute Photometry for Emission Line Filters The narrow band filters in NICMOS are intended primarily for observations of emission or absorption lines in sources Because the photometric conversion factors PHOTFNU and PHOTFLAM for all NICMOS filters are obtained from continuum observations of emission line free standard stars the flux in erg sec cm of an emission line is given by the expression Flux ine 1 054 x FWHM x PHOTFLAM x CR where FWHM is the full width half maximum of the equivalent gaussian filter to the narrow band filter used see Appendix 1 of the NICMOS Instrument Handbook and we have assumed that the continuum has been already subtracted from the total flux in the filter and that the line is centered in the filter If the emission line is not at the central wavelength of the filter the line flux will need correction for the filter transmission curve To estimate the variation in the absolute flux due to the positioning and width of the emission line in the filter bandpass the synphot task calcphot can be used as shown below See the Synphot User s Guide for additional help NICMOS 5 18 J Chapter 5 Data Analysis 5 3 5 Figure 5 1 Estimating Absolute Flux Variation sy gt epar calcphot obsmode nicmos 3 212n dn Instrument observation mode spectrum gauss 21200 40 unit 1E 13 flam S
40. System see STSDAS specfit task fit models to spectrum INTRO 3 37 spectra analysis tasks RAF INTRO 3 30 analysis STSDAS INTRO 3 24 analysis tasks in STSDAS INTRO 3 31 display INTRO 3 20 display STIS INTRO 3 21 extraction NICMOS grism NICMOS 5 51 fitting INTRO 3 34 specfit task INTRO 3 37 spectroscopy grism NICMOS NICMOS 3 4 splot task cursor commands INTRO 3 33 plot spectra INTRO 3 31 StarView observation logs APP C 9 STIS analysis preparing INTRO 3 27 display spectra INTRO 3 21 echelle spectra plotting INTRO 3 22 imset STSDAS tasks for INTRO 3 14 STSDAS INTRO 3 1 astrometry INTRO 3 11 astrometry in INTRO 3 10 described APP A 1 documentation INTRO 3 37 image analysis tasks INTRO 3 14 image display INTRO 3 4 INTRO 3 5 image display INTRO 3 8 image section INTRO 3 8 images INTRO 3 2 imset tasks INTRO 3 14 NICMOS calibration NICMOS 3 2 NICMOS software NICMOS 5 1 obtaining APP A 15 organization of INTRO 3 2 INTRO 3 3 photometry in INTRO 3 17 spectra analysis tasks INTRO 3 31 synphot database APP A 16 synthetic photometry INTRO 3 19 tables INTRO 3 4 suffix see files naming conventions support file NICMOS NICMOS 2 2 NICMOS 2 9 synphot database obtaining APP A 16 synphot package synthetic photometry INTRO 3 19 synthetic photometry see synphot Index HZ NICMOS 7 T table FITS INTRO 2 9 STSDAS INTRO 3 4 targe
41. V3 Axis peak to peak milli arcsec Recentering events occur when the spacecraft software decides that shaking is too severe to maintain lock The FGS will release guide star control and within a few seconds reacquire the guide stars It is assumed the guide stars are still within the FGS field of view During the recentering time INDEF will be written to the OMS table Recentering events are tracked in the OMS header file Be careful when interpreting Loss of Lock and Recentering events that occur at the very beginning or at the end of the OMS window The OMS window is larger than the observation window These events might not affect the observation since the observation start time will occur after the guide stars are acquired or re acquired and the observation stop time may occur before the Loss of Lock or Recentering event that occurred at the end of an OMS window The sgraph commend in the stsdas graphics stplot package will plot time vs jitter along the direction of HST s V2 axis see figure C 4 cl gt sgraph x3y60102j jit fits seconds si_v2_avg APP C 14 Appendix C Using Observation Logs Figure C 4 Plotting Jitter Along V3 Axis NOAO IRAF V2 11EXPORT lallo squonk stsci edu Thu 13 55 32 18 Sep 97 squonk stsci edu data squonk 1 day118 jitterdata x3y60102j_jit fits T T mrri my 001 0 4 7 J 2 2 4 a eg 4 gt s 1 00
42. WWW pages for updates or examine the in flight test photometry of red stars themselves Non Zero Zeroth Read Correction for Bright Sources The problem of the non zero zeroth read for bright sources was discussed in section 3 3 ZSIGCORR and section 4 3 2 If significant signal from an object is present in the zeroth read then this was not properly taken into account in the nonlinearity corrections made for data processed by the OPUS pipeline before 11 November 1997 It is advisable to reprocess the data with the most recent version of the calibration software which includes an additional step ZS IGCORR to account for this zero read signal correction When reprocessing such data calnica version 3 3 or greater will automatically apply this step to all MULTIACCUM mode observations if both ZOFFCORR and NLINCORR are also being performed All data retrieved from the Archive via OTFR after 26 September 2001 are automatically processed with this step Magnitudes and Photometric Systems Transformations AS was previously mentioned NICMOS data are calibrated in units of Jy or Jy arcsec for flux densities and surface brightnesses respectively The filter bandpasses do not exactly match those of ground based JHK filters and therefore if you wish to derive standard JHK magnitudes from NICMOS data then it will be necessary to apply a color term correction The recommended NICMOS JHK analog system is obtained using the F110W F160W and F222M filters
43. a NICMOS science image This zeroth readout is transmitted to the ground with MULTIACCUM data but is directly subtracted from the final readouts on board the telescope for all the other readout modes Due to physical limitation in the readout speed the zeroth read happens 0 203 seconds after the reset of the detector NICMOS does not have a shutter and therefore when a bright source is being observed a non negligible amount of charge may accumulate on the detector by the time the zeroth read is performed enough to significantly affect detector nonlinearity However zeroth read subtraction is the first step of the calibration processing for MULTIACCUM data ZOFFCORR in calnica and is automatically done on board the telescope from the final read in a ACCUM exposure The zeroth read signal information is therefore lost before nonlinearity correction NLINCORR in calnica is performed and for bright sources this correction may therefore be inaccurate Cures In November 1997 an additional step was added to the calnica pipeline processing software version 3 0 and higher to account for this zero read signal correction and an additional keyword ZSIGCORR was included in NICMOS image headers to control this step The ZSIGCORR step computes an estimate of the number of counts for each pixel in the zeroth readout of a MULTIACCUM based on the count rate measured later in the exposure This information is then used in the NLINCORR step to estimat
44. a count rate of 1 DN sec PHOTFNU is given in units of Jy sec DN and PHOTFLAM in units of ergs cm DN Because NICMOS calibrated data are given in countrate ie DN sec the countrate to flux conversion is simply achieved by multiplying the countrate by the PHOTFNU or PHOTFLAM value depending on which units are desired for the final calibrated image A fundamental challenge in calibrating NICMOS photometry is the inherent uncertainty in absolute flux calibration in the near infrared whether from the ground or from space Unlike the situation at optical wavelengths there really are no absolutely calibrated spectrophotometric flux standards at near infrared wavelengths Ground based photometric Photometric Calibrations W NICMOS 5 7 calibration observations are mostly limited to relative magnitude determinations in more or less standard bandpasses JHK defined by atmospheric absorption windows But the absolute flux calibration of primary infrared standards has generally been based on reference to some assumption that a particular type of standard star e g solar type stars AO stars or white dwarfs has a spectrum similar to something else that is believed to be well understood such as the Sun or a well calibrated stellar atmosphere model As an example see Campins Rieke amp Lebofsky 1985 who used the solar analog approach to derive absolute flux calibrations in the near infrared These calibrations are uncertain at
45. although the F110W filter especially is quite different from the standard J bandpass specifically it is much broader and bluer Synthetic color terms can be computed using synphot given real or model spectra for an astronomical source and the NICMOS and ground based filter bandpasses see for example Holtzman et al 1995 PASP 107 1065 where a similar procedure was used to derive color terms for WFPC2 photometry 5 3 4 Photometric Calibrations I NICMOS 5 17 Also as part of the Cycle 7 absolute photometry program we observed a few blue stars white dwarfs intermediate color stars solar analogs and very red stars covering a large range in color table 5 4 The calibrated data are available from the archive for users who wish to derive their own color terms to transform their HST fluxes into any ground based system The ground based photometry given in the table below is based on preliminary and incomplete measurements and will be updated when the final NICMOS photometric calibrations are completed Table 5 4 List of Stars for Photometric Transformations Name H J H H K Status Program IDs G191 B2B 12 6 0 10 0 14 Primary standard white dwarf 7691 7816 P330E 11 6 0 28 0 07 Primary standard solar analog 7691 7816 OPH S1 73 1 53 0 94 Primary standard red standard 7049 7691 GD153 Secondary standard white dwarf 7904 7816 P177D 12 0 0 28 0 06 Secondary standard solar analog 7904 7816 CSKD 12 9 5 2 08 0 89
46. an associated block of binary parameters called the Group Parameter Block GPB The sizes and datatypes of the data arrays and group parameters in 1 GEIS files are also commonly referred to as STSDAS images GEIS File Format HJ INTRO 2 13 each group of a GEIS file are identical Figure 2 2 depicts the structure of a GEIS data file graphically The binary content of GEIS files is machine dependent Copying GEIS files directly from one platform to another e g from a VAX to a Sun may result in unreadable data Figure 2 2 GEIS File Structure 80 byte card images Header File HHH Data File HHD im f Data Parameters Data Parameters Data Parameters Group 1 Group 2 Group 3 2 3 1 Converting FITS to GEIS The STScI archive stores and distributes datasets from FOC FOS FGS GHRS HSP WF PC 1 and WFPC2 in a special archival FITS format We highly recommend that users convert these datasets back into their native GEIS format before working with them Your data must be in GEIS format for you to use many of the STSDAS software tools developed specifically for analysis of these data It is important to use the strfits task found in stsdas fitsio or in tables fitsio to perform the conversion from archival FITS format to the GEIS format because the data processing pipeline employs a special convention for mapping GEIS files to FI
47. an operating system level command i e Unix or VMS commands from within the IRAF CL precede the command with an exclamation point This procedure is called escaping the command For example st gt system_command Piping and Redirection You can run tasks in sequence if you desire with the output of one task being used as the input for another This procedure called piping and is done by separating commands with a vertical bar using the following syntax st gt taskl filename task2 For example if a particular task prints a large volume of textual output to the screen you will often want to pipe it to page which allows you to read the output one page at a time st gt taskI filename page Appendix A IRAF Basics IJ APP A 7 You can also redirect output from any task or command to a file by using the greater than symbol gt as follows st gt command gt outputfile Background Tasks To run a task as a background job freeing your workstation window for other work add an ampersand amp to the end of the command line like this st gt taskname amp A 2 3 Getting Help This section describes e How to use IRAF s on line help facility e How to find a task that does what you want see Finding Tasks on page A 8 On Line Help You can get on line help with any IRAF task or package by using the help command which takes as an argument the task or package nam
48. and a variety of other features on plots Different line weights font styles and feature shapes are available enabling you to create complex plots Figure 3 5 shows a sample plot created in igi however because igi is a complete graphics environment in itself it is well beyond the scope of this document You can learn more about igi in the G Reference Manual available through the STSDAS Web pages INTRO 3 24 Chapter 3 STSDAS Basics Figure 3 5 Sample igi Plot Observed versus Theoretical Data 104b ae D EEA R 10 bk 5 100 amp i E 0 1 i i 0 10 20 30 40 50 Sample Number 3 5 Analyzing HST Spectra 3 5 1 This section describes some IRAF STSDAS tasks that can be used for analyzing and manipulating spectral data Some of these tasks operate directly on HST data files created by the pipeline However a number of the most useful IRAF tasks such as splot require special preparations of data other than STIS two dimensional spectra Before discussing these tasks we will first show how to recast your data into forms that are more generally accessible Preparing FOS and GHRS Data The FOS and GHRS data reduction pipelines store fluxes and wavelengths in separate files In GEIS format the c1h file contains the flux information and the cOh file contains the wavelength information Because IRAF tasks generally require both the flux and wavelength information to reside in the same file yo
49. are non ideal 7 Q and U are correlated when calculating P and 0 Therefore covariances must be taken into account when calculating the errors For the degree of polarization the covariance is oP of 28 03 2B 02 22 4 EOL Ado aU 20 o 37 50 28 7 50 2 00 50 50 1Q gI aO TU gI aU 2U 90 AU where P_ NQ U 0P_ Q ee A L m ol T dO IP U oU IPU The covariance for the position angle is gt Die z 240 201 2 Sap 726 SE Sou 00 aU 3Q U where dpp U pp 1 Q 2 aU 2 5 1 oF 5 i o Q Q 5 7 3 A Useful Script for Polarization Analysis An interactive IDL program to derive relevant parameters from NICMOS polarization images has been developed The IDL program reads three images taken with three polarizers from NIC1 or NIC2 produces five images as output The output images are Grism Data Reduction W NICMOS 5 47 e q fit and u fit two images representing the Stokes parameters e i fit the total intensity e pfit the degree of polarization and e theta fit the polarization angle Polarization vectors or contour maps can be superimposed over the intensity image The program is available from the STScI NICMOS web site under software tools and is described in more detail in Mazzuca amp Hines NICMOS ISR 99 004 User s Guide to Polarimetric Imaging Tools 5 8 Grism Data Reduction The NICMOS camera 3 grisms permit multi object slitless low resolution spectroscopy
50. are used In order to disable ILLMCORR the keyword must be changed in the association table header itself not in the primary image header of the association table FITS file This must be done with the tables parkey task not with hedit See the highlighted note at the end of section 3 5 2 for how to do this Ordinarily it is simplest to just leave IELMCORR PERFORM and use the dummy reference files The constant background signal level is estimated and removed as follows 1 With chop patterns the median and average deviation of the signal in the image at each chop position is computed In addition to excluding bad and source flagged pixels the calculation of the median also uses iterative sigma clipping to reject outliers 2 With dither only patterns or with multiple exposure single pointings the median and average deviation of each target image is computed The result for each image is compared to the background estimate provided by calnica which is in principle stored in the BACKEST1 header keyword of each image The value computed by calnicb is accepted if it is less than 5o deviant from that of calnica otherwise the calnicb value is assumed to be biased by the presence of sources and the calnica value is substituted for it Note however that nor mally the value of BACKEST1 would be populated by the BACK NICMOS 3 22 Chapter 3 Calibration CALC step of calnica which has never been implemented see section 3 3 Therefor
51. as a function of time during the lifetime of the instrument The changes were most rapid during the orbital verification period and approximately the first 100 days of instrument operations then slowed with only small variation thereafter The pixel scale was monitored regularly throughout the lifetime of the instrument A tabular and graphical record of these measurements for all three cameras can be found on the STScI NICMOS WWW pages at http hst stsci edu nicmos performance platescale NICMOS 5 20 Chapter 5 Data Analysis 5 4 2 5 4 3 The NICMOS history tool see section 5 2 will also provide the scale information for any given observation These sources should be consulted before transforming pixel coordinates in the image to arcseconds X and Y Pixel Scale Differences The NICMOS arrays are slightly tilted relative to the focal plane and therefore the NICMOS pixel scales along the X and Y axes of each camera are slightly different i e projected on the sky the pixels are actually slightly rectangular not square This is a small effect the X Y scale ratios Sy Sy are approximately 1 0039 1 0086 and 1 0030 for cameras 1 2 and 3 respectively in the sense that the X scale in arcseconds per pixel is larger than the Y scale in each case It amounts to 1 to 2 pixels extra width in the X direction relative to Y over the field of view of the cameras and for precision astrometry or when registering NICMOS images to dat
52. correction to pixels with signal below their defined saturation levels However it applies no correction to pixels in the high signal regime but rather flags them in the DQ image as saturated DQ value 64 This step uses the NLINFILE reference file which consists of a set of images containing the c c2 and c3 correction coefficients and their variances at each pixel The NODE 2 extension of the NLINFILE sets the saturation value for each pixel Error estimates on the correction applied to non saturated pixels are propagated into the ERR images of all imsets processed Data quality flags set in the NLINFILE are also propagated into the processed DQ images There is one NLINFILE per detector Early versions of NICMOS non linearity correction used a linear cor rection scheme rather than the 2nd order parameterization that is now employed Starting in calnica v3 3 the NLINCORR step was updated to accommodate the 2nd order correction but is back wards compatible such that old NLINFILEs using the linear correc tion may still be used if desired New reference files have been created that include these higher order corrections Additionally the nonlin earity reference files include a NODE extension This sets the data value below which no nonlinearity correction is applied It now appears instead that the NICMOS arrays are somewhat nonlinear at all count levels In the new NLINFILEs therefore the NODE 1 val ues are uniformly se
53. ctools package extracts one or more spectral orders from a STIS table fits a polynomial dispersion INTRO 3 28 Chapter 3 STSDAS Basics solution to each wavelength array and stores the spectra in an output file in original IRAF format OIF using the multispec WCS This task is layered upon the mkmultispec task which performs a similar operation for FOS and GHRS calibrated spectra see mkmultispec on page 3 25 Most of the parameters for tomultispec echo those for mkmultispec As a helpful navigational aid the STIS spectral order numbers are written to the corresponding beam numbers in the multispec image the aperture numbers are indexed sequentially starting from one You can choose to fit the dispersion solution interactively but the default fourth order Chebyshev polynomial will likely suffice for all STIS spectral orders except for prism dispersed spectra However you cannot use the interactive option if you are selecting more than one order from the input file For example if you want to write all spectral orders from the STIS file myfile xld fits toa multispec file cl gt tomultispec myfile_ xld fits new_ms imh Note that the imh suffix on the output file specifies that the output file is to be an OIF file This format is similar to GEIS format in that it consists of two files a header file imh and a binary data file pix The output format for tomultispec will always be OIF If you want to select
54. data as well Similarly stellar images through the shorter wavelength filters where the telescope diffraction limit is smaller show a greater variation due to this effect than do longer wavelength data In addition the intrapixel sensitivity variations can introduce complications for measuring image centroids pulling the centroid away from pixel corners and edges toward the center of the pixel The effects of intrapixel sensitivity variations and possible approaches to correcting NIC3 point source photometry are discussed in two useful references NICMOS ISR 99 005 Storrs et al available from the STScI WWW pages and a paper by Tod Lauer 1999 PASP 107 p 1434 Storrs et al derive a photometric correction for Camera 3 F110W and F160W stellar images based on a sharpness ratio defined as the ratio of the flux in the peak pixel to that in the integrated PSF This method is simple to apply and avoids uncertainties due to centroiding errors Lauer derives a NICMOS 5 14 J Chapter 5 Data Analysis two dimensional pixel response map which can be used to correct photometry if the position of a point source can be measured accurately Intrapixel sensitivity variations should have substantially less effect on spatially extended sources In general given well dithered data sampling many different sub pixel positions the variations due to intrapixel sensitivity should average out but given the rather large amplitude of the effect f
55. e On data storage media written at STScI from the HDA The options are Exabyte and DAT tapes and will include CDs and DVDs in the future To retrieve data electronically you must first register as a MAST user HST Principal Investigators PIs are not automatically registered If you have not recently retrieved data you should register or renew your registration before retrieving data from the HDA PIs should register before their observations are made GTO and GO observations normally remain proprietary for a period of one year which means that during this period 1 MAST currently includes data from HST FUSE IUE EUVE ASTRO HUT UIT WUPPE ORFEUS BEFS IMAPS TUES Copernicus and ROSAT Data from the FIRST radio survey Digital Sky Survey DSS and Sloan Digital Sky Survey SDSS are also available 2 By 2002 registration will no longer be required for public non proprietary data INTRO 1 1 INTRO 1 2 J Chapter 1 Getting HST Data y other registered users cannot retrieve them without authorization from the PI All calibration observations as well as observations made as part of the Public Parallel programs are immediately public All observations made as part of the Treasury Programs begun in Cycle 11 will either be immediately public or have only a brief proprietary period The HST section of MAST also contains several Prepared fully reduced data sets including the Hubble Deep Fields the Hubble Medium Deep Survey
56. effect on the flux data at all is to use the mkmultispec task This task places wavelength information into the headers of your flux files according to the IRAF multispec format World Coordinate System WCS The multispec coordinate system is intended to be used with spectra having nonlinear dispersions or with images containing multiple spectra and the format is recognized by many tasks in IRAF V2 10 or later For a detailed discussion of the multispec WCS type help specwcs at the IRAF prompt The mkmultispec task can put wavelength information into the flux header files in two different ways The first involves reading the wavelength data from the cOh file fitting the wavelength array with a polynomial function and then storing the derived function coefficients in the flux header file clh in multispec format Legendre Chebyshev or cubic spline spline3 fitting functions of fourth order or larger produce essentially identical results all having rms residuals less than 104 A much smaller than the uncertainty of the original wavelength information Because these fits are so accurate it is usually unnecessary to run the task in interactive mode to examine them If there are discontinuities in the wavelengths which could arise due to the splicing of different gratings you should run mkmultispec in interactive mode to verify the fits INTRO 3 26 Chapter 3 STSDAS Basics Y Because mkmultispec can fit only simple types of
57. flux data value pairs or wavelength flux error value triples see imtab on page 3 26 Table 3 7 Tasks in the STSDAS fitting Package Task Purpose function Generate functions as images tables or lists gfitld Interactive 1 d linear curve fit to images tables or lists i2gaussfit Iterative 2 d Gaussian fit to noisy images script nfitld Interactive 1 d non linear curve fit to images tables or lists ngaussfit Interactive 1 d multiple Gaussian fit to images tables or lists n2gaussfit 2 d Gaussian fit to images prfit Print contents of fit tables created by fitting task When using tasks such as ngaussfit and nfitld you must provide initial guesses for the function coefficients as input to the fitting algorithms You can either specify these initial guesses via parameter settings in the task s parameter sets psets or enter them interactively For example suppose you want to fit several features using the ngaussfit task Using the default parameter settings you can start the task by typing fi gt ngaussfit n4449 hhh linefits tab This command reads spectral data from the image n4449 hhh and stores the results of the line fits in the STSDAS table Linefits tab After you start the task your spectrum should appear in a plot window and the task will be left in cursor input mode You can use the standard IRAF cursor mode commands to rewindow the plot resticting your display to the region around a
58. for objects with extreme colors The color of the internal flatfield lamps may not match that of the sky background or indeed of many astronomical sources In most cases this should only affect NICMOS 4 26 Chapter 4 Anomalies and Error Sources photometry by a few percent but concerned users may wish to experiment with constructing customized spectrally weighted flatfields These can be constructed from linear combinations of and interpolations between existing NICMOS narrow band flat fields as described in Storrs Bergeron and Holfeltz 1999 ISR NICMOS 99 002 One situation where the color dependence of the flat fields may have a visibly noticeable effect is on the flatfielding of the sky background The background has a significantly different spectrum than the flat field lamps particularly at gt 1 8um where thermal emission from the telescope and instrument become important After dividing by ordinary internal lamp flats flat field residuals may still be present in the sky background Unfortunately in practice it is difficult to separate these from the characteristic variations induced by the pedestal effect discussed above in section 4 1 2 Pedestal removal routines like pedsky see section 4 1 5 key off these residual flat field variations and depend on having an accurate model of the spatial structure of the sky If actual observed sky frames are not available then synthetic color dependent flats may be useful when runnin
59. hhh This command will add 77 0 to the data in group 10 of the file indata hhh and will write the output to a new single group file called outdata hhh Any operation performed on a single group of a multigroup GEIS file results in an output file containing a single group Specifying an Image Section If you wish to process only a portion of an image you can specify the image section after the group specification in the following manner cl gt imarith indata hhh 2 100 199 200 399 32 0 outdata hhh This command extracts a 100 by 200 pixel subsection of the image in the second group of the file indata hhh multiplies this data by a factor of 32 0 and stores the result in a new output file outdata hhh which is a 100 by 200 pixel single group GEIS file Printing Header Information As discussed in the previous section the task imheader extracts and prints information about the GEIS image This task reports the image 2 3 4 GEIS File Format HJ INTRO 2 17 name dimensions including the number of groups pixel type and title of the image when it is run in default mode For example cl gt imhead indata hhh indata hhh 1 64 500 real INDATA 1 64 The output line indicates that indata hhh is a multigroup GEIS file which contains 64 groups of images each consisting of a spectral array 500 pixels in length The data type of the values is real floating point Note that since no group designation was pr
60. is known as an image set or imset A science data file can contain one or more imsets For example an individual NICMOS exposure obtained with the ACCUM mode will generate a raw fits file with one imset an_ individual MULTIACCUM exposure with n readouts will generate a _raw fits file and after calibration an _ima fits file containing n 1 imsets including the zeroth readout The _cal fits and mos fits files always contain one imset The insets of a MULTIACCUM exposure are stored in files from last to first The result of the longest integration time the last readout per Af formed on board occurs first in the file first imset the readout before the last is the second imset and so on the zeroth readout is the last imset Although the five science error data quality samples and integration time arrays associated with each imset are stored in a single file they are kept separate as five individual FITS image extensions within the file The order of the images in the FITS files is listed in table 2 1 and shown graphically in figure 2 1 and figure 2 2 The examples given in table 2 1 and figure 2 2 refer to a MULTIACCUM image multiple imsets while figure 2 1 refers to ACCUM and BRIGHTOBJ images one imset namely extensions 1 through 5 Each extension comes with its own header and each FITS file contains in addition a global or primary header primary header data unit or HDU The only contents of the primar
61. most tasks especially those specific to HST instruments can not It is therefore HIGHLY recommended that all waiver FITS files are converted back to the GEIS format by using the task strfits before further processing and analysis with IRAF STSDAS tasks CHAPTER 3 STSDAS Basics In this chapter 3 1 Navigating STSDAS 3 2 3 2 Displaying HST Images 3 4 3 3 Analyzing HST Images 3 9 3 4 Displaying HST Spectra 3 20 3 5 Analyzing HST Spectra 3 24 3 6 References 3 37 The Space Telescope Science Data Analysis System STSDA is the software system for calibrating and analyzing data from the Hubble Space Telescope The package contains programs called tasks that perform a wide range of functions supporting the entire data analysis process from reading tapes through reduction and analysis to producing final plots and images This chapter introduces the basics of STSDAS showing you how to display your data leading you through some simple data manipulations and pointing you towards more sophisticated tasks some of which are described in the instrument data handbooks STSDAS is layered on top of the Image Reduction and Analysis Facility IRAF software developed at the National Optical Astronomy Observatory NOAO Any task in IRAF can be used in STSDAS and the software is portable across a number of platforms and operating systems To exploit the power of STSDAS effectively you need to know the basics of I
62. of cmj _cmi fits Archived FITS file of cmi August 1995 to February 1997 jih jid Two dimensional histogram and header GEIS jit Three second averages IRAF table _jif fits Archived FITS file which bundles the jih Jid files _jit fits Archived FITS file of jit February 1997 onward _jif fits Two dimensional histogram FITS _jit fits Three second averages table FITS 1 After May 11 1995 the jit tables for exposures shorter than 6 seconds contain higher resolution one second average pointing data Appendix C Observation Log Files IJ APP C 3 Pointing and tracking information prior to October 1994 is not rou V tinely available Interested observers with data from this epoch can send E mail to help stsci edu C 1 1 Observation Log File Contents October 1994 version Observation logs created between October 1994 and August 1995 contain rootnamej cmh This ASCII header file contains the time interval the rootname averages of the pointing and spacecraft jitter the guid ing mode guide star information and alert or failure keywords Fig ure C 1 shows a representative observation log header file rootnamej cmj This table presents the data at the highest time res olution for the telemetry mode in use It contains the reconstructed pointing guide star coordinates derived jitter at the instrument aper ture and guiding related flags The intent is 1 to provide high time resolution jitter data for deconvolu
63. of the errors parameter which controls whether or not the task will estimate error values for the derived coefficients Because the process of error estimation is very CPU intensive it is most efficient to leave the error estimation turned off until you ve got a good fit and then turn the error estimation on for one last iteration Figure 3 6 and figure 3 7 shows the results of fitting the HB 4861A and ONI 4959 and 5007 A emission features in the spectrum of NGC 4449 The resulting coefficients and error estimates in parentheses are shown in figure 3 7 3 To see the online help for details and a complete listing of cursor mode colon com mands type help cursor INTRO 3 36 f Chapter 3 STSDAS Basics Figure 3 6 Fitting Hf and OIll Emission Features in NGC 4449 STScI IRAF V2 10EXPORT bustonse char Stsci edu Mon 09 26 04 21 Feb 94 func Gaussians low_rej 9 hi rej 0 niterate 1 grow 0 total 3240 sample 354 rejecte at deleted 0 RMS 5 8E 16 T I T T T 6 00E 14 z 5 00E 14 ra 4 00E 14 n4449 hhh 3 00E 14 2 00E 14 l 4800 4850 4900 4950 5000 5050 X Figure 3 7 Coefficients and Error Estimates function Gaussians coeffl 8 838438E 14 0 Baseline zeropoint fix coeff2 1 435682E 17 0 Baseline slope fix coeff3 1 854658E 14 2 513048E 16 Feature 1 amplitude var coeff4 4866 511 0 03789007 Feature 1 center var coeff5
64. of this chapter Cycle 7 and 7N data delivered to the observer or retrieved from the HST archive before 26 September 2001 were calibrated with the best instrument configuration specific reference files available at the time of the observation However updated or timely reference files sometimes do become available after the data were taken and first processed As one important example the DARK refrerence files were substantially updated and improved during and after Cycle 7 Improved software for calibration e g updates to both calnica and calnicb as well as new tasks external to the standard pipeline may also become available as our understanding of the instrument performance increases with experience For example the ZSIGCORR step of calnica was added part way through the lifetime of the instrument and BARSCORR was implemented in calnica version 3 3 released after the end of NICMOS operations Many data sets retrived from the archive during Cycle 7 have not had the ZSIGCORR step applied and none have had the BARSCORR correction Other improvements to the pipeline tasks were developed along the way and older data sets particularly those obtained during the first few months of the NICMOS on orbit operations will often benefit from reprocessing with the latest software and reference files After 26 September 2001 NICMOS data retrieved from the Archive are automatically reprocessed by OTFR using the latest pipeline software and calibration
65. on OMS files you can consult Appendix C or the STScI Observation Logs WWW pages at http www stsci edu ftp instrument_news Observatory obslog OL_1 html v PDQ Files The suffix pdq denotes Post Observation Summary and Data Quality Comment files PDQ files which contain predicted as well as actual observation parameters extracted from the standard header and science headers These files may also contain comments on any obvious features in the spectrum or image as noted in the OPUS data assessment or automatically extracted information about problems or oddities encountered during the observation or data processing These comments may include correction to the keywords automatically placed in the OMS files OCX Files The suffix ocx denotes Observer Comment Files OCX files which are produced by STScI personnel to document the results of real time commanding or monitoring of the observation along with keywords and comments Prior to April 17 1992 OCX files were not always archived separately and in some cases were prepended to the trailer file After early February 1995 OCX files were produced only when an observation was used to locate the target for an Interactive Target Acquisition At this time mission and spacecraft information were moved to the PDQ reports and the Observation Logs OMS jitter image and jitter table Trailer Files Trailer files suffix tr1 are FITS ASCII tables that log the processing of your d
66. or the other of the input tables so that the output table will be monotonically increasing or decreasing in wavelength Preparing STIS Spectra for Analysis Calibrated STIS spectra emerge from the pipeline either as two dimensional images _x2d files or as one dimensional spectra in tabular form _x1d files You can analyze calibrated two dimensional STIS spectra in IRAF as you would with any other long slit spectral image because their headers already contain the necessary wavelength information Tabulated STIS spectra can be analyzed directly using STSDAS tasks that understand the selectors syntax described in section 2 2 2 However to use IRAF tasks such as splot that rely on the multispec WCS or to use STSDAS tasks that do not understand three dimensional tables you will have to prepare your data appropriately This section describes two useful tasks for putting your data in the proper form e tomultispec This task is the STIS analog to mkmultispec described above It extracts STIS spectra from tables and writes them as IRAF spectral images with wavelength information in the header e txtable This task extracts specified data arrays from STIS table cells and places them in conventional two dimensional tables for easier access e tximage Extracts specified data arrays from STIS table cells and places them into 1 D images This task can write single group GEIS files tomultispec The tomultispec task in the stsdas hst_calib
67. particular spectral orders rather than writing all the orders to the multispec file you will need to use the selectors syntax To select only the spectrum stored in row nine of the input table the previous example would change to cl gt tomultispec myfile xld fits r row 9 new_ms imh Note that the double quote marks around the file name and row selector are necessary to avoid syntax errors To select a range of rows say rows nine through eleven cl gt tomultispec myfile_xld fits r row 9 11 new_ms imh You can also select rows based upon values in some other column For example to select all rows whose spectral order lies in the range 270 to 272 type cl gt tomultispec myfile_ xld fits r sporder 270 272 gt gt gt new_ms imh V V Analyzing HST Spectra W INTRO 3 29 The calibrated flux is extracted by default However other intensity data can be specified by setting the flux_col parameter Be careful not to restrict the search for matching rows too heavily Column selectors cannot be used with tomultispec Choose the type of fitting function for the tomultispec dispersion solu tion with care Using the table option which writes the entire wave length array to the image header for each order will fail if more than about three orders are selected This restriction results from a limit to the number of keywords that can be used to store the dispersion rela tion txta
68. pedestal signal searching for the amplitude which minimizes pixel to pixel variations Unlike pedsky however pedsub can optionally apply a spatial filtering function to each trial image in order to remove unwanted features or spatial frequencies i e the signal from objects that might bias the calculation of the pixel value spread The filtering options are median and mask which essentially carry out low pass and high pass filtering of spatial frequencies The mask option removes all large scale structure from the trial image leaving the RMS minimization process to operate only on the small scale pixel to pixel component of the flatfield signal This option can be effective when trying to measure and remove pedestal from e g images of large galaxies Pedsub has many other parameters and options which are fully described in the STSDAS help pages for the task These should be consulted carefully before using the task and the user may wish to experiment with combinations of these parameters in order to achieve the best results Using nicpipe biaseq and pedsky An Example Here we illustrate the use of the nicpipe biaseq and pedsky tasks with one example A similar sequence could be used with pedsub substituted for pedsky The raw data frame is n4yx23x0q_raw fits This is a NIC3 image taken with the SPARS64 readout sequence and NREAD 24 We might start by using the sampinfo task see section 5 1 to look at the details of the read
69. polynomial functions to wavelength data this method will not work well with FOS prism data because of the different functional form of the prism mode dis persion solution For prism spectra use the header table mode of mkmultispec see below or create an STSDAS table using imtab The other method by which mkmultispec can incorporate wavelength information into a flux file is simply to read the wavelength data from the cOh file and place the entire data array directly into the header of the flux c1h file This method simply dumps the wavelength value associated with each pixel in the spectrum into the flux header and is selected by setting the parameter function table To minimize header size set the parameter format to a suitable value For example using format 8 7g will retain the original seven digits of precision of the wavelength values while not consuming too much space in the flux header file Be aware that there is a physical limit to the number of header lines that can be used to store the wavelength array approximately 1000 lines This limit cannot be overridden Under ordinary circumstances this limitation is not an issue However if many spectral orders have been spliced together it may not be possible to store the actual wave length array in the header and a fit must be done instead imtab Another way to combine wavelengths with fluxes is to create an STSDAS table from your spectrum The imtab task in the S
70. reference files This is the easiest way to recalibrate your data However there are still situations where you may wish to reprocess your data locally using non standard reference files or software tools For example the NICMOS bias dark current and flat field structure are all functions of instrument temperature STScI has developed new WWW based tools for generating temperature specific DARK and FLAT reference files see section 4 1 5 which may improve the quality of your data reductions At present the only way to take advantage of these special darks and flats is to reprocess the data yourself locally although the NICMOS 3 24 Chapter 3 Calibration 3 5 2 NICMOS group is currently working on implementing temperature dependent dark correction automatically in the calnica pipeline Finally NICMOS data are subject to a variety of anomalies which may complicate the task of data reduction These are discussed extensively in chapter 4 In many cases procedures and software for handling these anomalies were not available when the observations were made or retrieved from the Archive If you notice unusual features in your data see e g the checklist at the start of chapter 4 or if your analysis requires a high level of accuracy you may wish to explore whether a better set of calibration reference files exist than those that were used to process your data or if additional processing steps may be needed If better files are availa
71. salgorithm auto interactive rmedian The end product n4yx23x0q_ped fits is the fully processed and pedestal corrected image Other Pedestal Removal Software The STScI NICMOS group will continue to explore methods for measuring and removing bias offsets from NICMOS data In particular as of the time of this writing we are investigating the possibility of automatically implementing the biaseq and pedsub procedures in the calnica pipeline Users should check the NICMOS web pages and STANs for updates on this effort In addition there are other freelance packages for NICMOS data reduction One example is Brian McLeod s NICRED package McLeod 1997 in the proceedings for the 1997 HST Calibration Workshop ed S Casertano et al p 281 which offers a general suite of NICMOS data reduction tools including routines which estimate and subtract pedestal Ultimately there are similarities in the pedestal removal methods used by pedsky pedsub and the NICRED algorithms and therefore it should be possible in principle to unify them in a single task NICMOS 4 20 Chapter 4 Anomalies and Error Sources 4 2 Bars Bars figure 4 5 are another bias related artifact They appear as narrow stripes that cross the quadrants of an array and occur identically in all 4 quadrants at the same rows columns in each They arise from electrical cross talk in the detector lines when one camera reads out while the auto flush pattern is executing in o
72. set of extensions associated with a given readout will have a unique EXTVER value running from 1 up to the total number of readouts in that particular file To list the header of the second science image in a MULTIACCUM sequence in place of the command line above one could instead type cl gt imheader n0g70106t_cal fits sci 2 long page In general to access a particular image extension append the name and version number of the desired extension in square brackets to the end of the file name The EXTNAME value is specified first then the EXTVER value separated by a comma Indeed the use of the keywords EXTNAME and EXTVER is not limited to the task imheader but can be used in all IRAF tasks The primary header data unit in a NICMOS FITS file does not contain the EXTNAME or EXTVER keywords The absolute extension num ber 0 zero refers to the primary header Working with NICMOS Files IJ NICMOS 2 19 If a calibration keyword needs to be changed the IRAF STSDAS chealpar task can be used For instance to modify the flatfield calibration switch from PERFORM to OMIT in a given data file the following command can be given cl gt chcalpar n0g70106t_raw fits The parameter set or pset list appropriate for the image will appear and the calibration keyword can be modified The operation performed with chealpar can be equivalently performed although in a more cumbersome way with the general IRAF task hedit in thi
73. status of the request i e how many files have been transferred and any errors that have occurred can be checked on a Web page that will be given in the acknowledgment message Using StarView to Retrieve Calibration Files and Proposal Information StarView allows several additional types of searches of the HDA besides the Quick Search option described above These can be selected from the Searches menu bar at the top of the StarView screen One such search option is by instrument This is necessary for identifying calibration reference files As an example selecting the option WFPC2 OTFR under the Instrument and WFPC2 sub menus of the Searches menu and then INTRO 1 10 Chapter 1 Getting HST Data 1 2 5 entering M87 under Target Name in the qualifications box brings up the screen shown in figure 1 3 This screen shows all the calibration images and files applied by OTFR to the first file in the set of WFPC2 images of M87 as well as whether the application of these files was performed or omitted in the calibration pipeline This is the same set of images found by the Quick Search query described above and the same information for the other datasets from this search can be found using the Previous Next and Scan buttons Once these calibration images have been identified further information on them can be obtained For example taking the name of the flat field file found in the above search and entering it into the WFPC2
74. the chcalpar task in the hst_calib ctools package of STSDAS or with the hedit task in the IRAF images package The calibration switch keywords reside only in the primary header of NICMOS FITS files Therefore it is critically important to specify extension number zero when passing file names to tasks like hedit to modify these keywords For example to modify calibration keywords in the file n3xe0lbhm_raw fits be sure to use the name n3xeOlbhm_raw fits 0 as input If you specify any other extension number the keywords you modify will end up getting written into the header of that extension instead where calnica will not find them The chcalpar task takes a single input parameter the name s of the raw data files to be edited When you start chealpar the task automatically determines that the image data are from NICMOS and opens a NICMOS specific parameter set pset that will load the current values of all the calibration related keywords To edit the calibration keyword values 1 Start the chealpar task specifying the image s in which you want to change keyword values Note that with chcealpar it is not necessary to append the primary header extension 0 to the image name If you specify more than one image for example using wildcards the task will read the initial keyword values from the first image in the list For example you could change keywords for all NICMOS raw NICMOS 3 26 Chapter 3 Calibration science images
75. the observation to center the target under the occulting spot Each 256 x 256 detector array is divided into four 128 x 128 quadrants each of which is read out by an amplifier at the corner of the quadrant There are four amplifiers in each camera Unlike CCDs infrared array pixels are read independently problems like charge transfer efficiency or bleeding are not present The three cameras operate independently optical elements integration times and readout modes can be different in each NICMOS 1 4 Chapter 1 Instrument Overview 1 2 Detector Readout Modes NICMOS does not have a physical shutter mechanism and exposures are obtained through a sequence of reset and read operations In particular a typical exposure will be the product of the following steps 1 Array reset the pixels are set to the bias level 2 Array read the charge in each pixel is measured and stored in the on board computer s memory This read is performed immediately after the reset and contains the reference level for the exposure zeroth read In practice the readout is performed 0 203 seconds after the reset implying that it represents a finite though very short exposure This readout is performed non destructively the charge in each pixel is left intact 3 Integration NICMOS integrates for the user specified time 4 Array read the charge in each pixel is measured and stored in the on board computer s memory Again the readout is non
76. to define which devices are used for certain operations For example your terminal type default printer and the disk and directory used for storing images are all defined through environment variables Environment variables are set using the set command and are displayed using the show command Table A 2 lists some of the environment variables that you might want to customize APP A 12 lf Appendix A IRAF Basics Table A 2 Environment Variables Variable Description Example of Setting printer terminal stdplot stdimage stdgraph clobber imtype Default printer for text Terminal type Default printer for all graphics output Default terminal display setting for image output most users will want this set to either imt512 or imt800 Default graphics device Allow or prevent overwriting of files Default image type for output images imh is original IRAF format hhh is STSDAS GEIS format set set set printer 1p2 term xterm stdplot ps2 stdimage imt800 stdgraph xterm clobber yes imtype hhh If you are working with GEIS files you should set imtype to hhh If you are working with STIS and NICMOS data in FITS files you can set imtype to fits You can set your environment variables automatically each time you login to IRAF by adding the appropriate commands to your login cl file Use your favorite text editor to specify each var
77. to peak milli arcsec V3_RMS 14 3 V3 Axis RMS milli arcsec V3_P2P 53 6 V3 Axis peak to peak milli arcsec RA AVG 244 01757 Average RA deg DEC_AVG 20 63654 Average DEC deg ROLL AVG 280 52591 Average Roll deg SLEWING T Slewing occurred during this observation Appendix C Using Observation Logs J APP C 13 C 3 4 High Jitter The spacecraft may shake during an observation even though the guiding mode is FINE LOCK This movement may be due to a micro meteorite hit jitter at a day night transition or for some other unknown reasons The FGS is quite stable and will track a guide star even during substantial spacecraft motion The target may move about in an aperture but the FGS will continue to track guide stars and reposition the target into the aperture For most observations the movement about the aperture during a spacecraft excursion will be quite small but sometimes especially for observations with the spectrographs the aperture may move enough that the measured flux for the target will be less than a previous group Check the OMS header keywords V2_RMS V3_RMS for the root mean square of the jitter about the V2 and V3 axis The following list of cmh header keywords is an example of typical guiding rms values V2_RMS V2_P2P V3_RMS V3_P2P LINE OF SIGHT JITTER SUMMARY 2 6 V2 Axis RMS milli arcsec 23 8 V2 Axis peak to peak milli arcsec 2 5 V3 Axis RMS milli arcsec 32 3
78. to the accumulating signal in the MULTIACCUM to derive the source background count rate with a rejection procedure designed to eliminate transient cosmic ray events see section 3 3 and section 4 7 A varying bias level can improperly trigger the CRIDCALC cosmic ray rejection or reduce its sensitivity to real cosmic ray events Secondly the net bias change over the course of the exposure results in an additive offset different in each quadrant when the MULTIACCUM sequence is reduced to a single count rate image the _cal fits file by CRIDCALC When the image is flatfielded this undesired additive offset is then modulated by the flatfield and appears as an inverse flatfield pattern in the final reduced data For illustration consider an image where the incident astronomical flux sources plus sky background is given by S x y This is modulated by the spatially dependent quantum efficiency or flatfield Q x y To this is added a quadrant bias offset By which may be different in each quadrant Here we neglect all other sources of bias and dark current assuming that they can be adequately removed by standard processing The recorded raw image is x y I x y S x y x O x y Bg If this image were then divided by the flatfield or to follow the STScI pipeline convention multiplied by the inverse flatfield the result would be Ixy Oxy S x y By x O x y NICMOS Dark Current and Bias IJ NICMOS 4 9 Thus the d
79. toolbox imgtools mstools This package contains tools for working with FITS image extensions in particular STIS and NIC MOS image sets imsets e stsdas analysis This package contains general tasks for image anal ysis such as Fourier analysis and dither Tables Several of the analysis packages in STSDAS including calibration pipeline tasks create output files in STSDAS table format which is a binary row column format or in FITS binary table format ASCII format tables are also supported for input only The STSDAS User s Guide describes the STSDAS table format in detail Tasks in the ttools package or in the external tables package can be used to read edit create and manipulate tables For example e tread displays a table allowing you to move through it with the arrow keys e tprint displays a table e tcopy copies tables e tedit allows you to edit a table Many other tasks in ttools perform a variety of other functions See the online help for details 3 2 Displaying HST Images This section will be of interest primarily to observers whose datasets contain two dimensional images as it explains e How to display images in IRAF using the display task e How to display subsections of images Observers viewing WF PC 1 and WFPC2 data may wish to remove cosmic rays before displaying their data The FOC photon counting hardware does not detect cosmic rays at easily as CCDs the NICMOS pipeline automatically remove
80. updated values The target location and slew values of the most recent target acquisition will be reflected in following observations until the next acquisition executes or until the values are re initialized to zero These values are not initialized during normal operation of NICMOS As presented the keyword values are scaled ENGINEERING units and not in pixels or arcseconds They must be converted from ENGINEERING units to DETECTOR and IMAGE coordinates Target Position in Detector Coordinates The target position coordinates can be converted into DETECTOR coordinates by dividing by 256 However the slew values are written in 2 s compliment A value less than 32757 is positive while a value larger than 32757 is negative Slew values need to be divided by 128 during the conversion into DETECTOR coordinates For example the following target and slew values were obtained from an SPT file and converted to DETECTOR coordinates 5 NICMOS Instrument Science Report NICMOS ISR 98 012 Coronagraphic Reductions IJ NICMOS 5 33 gt hedit n4q832nrq_spt fits 1 NXCENT NYCENT NOFFSETX gt gt gt NOFFSETY n4q832nrq_spt fits 1 NXCENT 31418 n4q832nrq _spt fits 1 NYCENT 20655 n4q832nrq spt fits 1 NOFFSETX 10101 n4q832nrq _spt fits 1 NOFFSETY 52259 NXCENT 31418 0 256 0 122 726 NYCENT 20655 0 256 0 80 683 NOFFSETX 10101 0 128 0 78 914 NOFFSETY 52259 0 65535 0 128 0 103 718
81. when doing this First on orbit darks are affected by pedestal effects Care must be taken when averaging frames particularly with sigma rejection schemes since the DC bias level of a given quadrant in a given readout may vary considerably from image to image The average dark image will still have some mean pedestal value in it Second one should be careful to examine all dark frames used for the average and to discard images which are adversely affected by bright object and SAA induced persistent signal see section 4 6 2 below Finally because shading is temperature dependent care should be taken to combine darks taken at the same detector temperature within approximately 0 1 degrees K as the observations for which they will be used Detector temperatures are stored in the NDWTMP11 and NDWTMP13 keywords in the _sptfits files For Cameras I and 2 use NDWTMP11 for Camera 3 use NDWTMP13 These keywords are incorrectly labelled in some NICMOS _spt fits headers ACCUM and BRIGHTOBJ Mode Darks In principle ACCUM mode allows the user to specify any of a large number 173 to be precise of possible exposure times ranging from 0 57 to 3600 seconds and either 1 or 9 initial and final readouts NREAD As was discussed above the various components of the DARK reference files e g bias shading linear dark current and amplifier glow depend not only on the integration time but on the number of readouts and the readout delta
82. worked out exercise concern ing drizzling with NICMOS data 3 4 1 Input Files Three pieces of input data are needed by calnicb 1 The association table assoc_id_asn fits this is a table contain ing the list of members in the association and relevant information on the association type as given in table 3 1 Table 3 1 Columns of the Association Table input to calnicb Column Name Meaning MEMNAME Rootname PPPSSOOT of each image in the association MEMTYPE Role or type of each member EXP TARG input exposure for target EXP BCKn input exposure of n th background for chop patterns PROD TARG output product containing target PROD BCKn output product containing n th background for chop patterns MEMPRSNT Flag indicating whether or not a member is present needed by the STScI auto matic pipeline processing The table extension header of the assoc_id_asn fits file also con tains the keywords which control the background illumination pattern correction ILLMCORR The keywords used are ILLMCORR NICMOS 3 18 Chapter 3 Calibration whether or not the correction is to be performed and ILLMFILE reference file name for the illumination correction These are explained in chapter 2 and discussed further in section 3 4 3 The input calibrated images ippssoot_cal fits the science data images which are part of the association as listed in the first column of the association table The i
83. 000 Pixel affected by grot on the detector 32 0000 0000 0010 0000 Defective hot or cold pixel 64 0000 0000 0100 0000 Saturated pixel 128 0000 0000 1000 0000 Missing data in telemetry 256 0000 0001 0000 0000 Bad pixel determined by calibration 512 0000 0010 0000 0000 Pixel contains Cosmic Ray 1024 0000 0100 0000 0000 Pixel contains source see section 3 4 2048 0000 1000 0000 0000 Pixel has signal in Oth read see section 3 3 4096 0001 0000 0000 0000 User flag 8192 0010 0000 0000 0000 User flag 16384 0100 0000 0000 0000 Reserved 1 Most significant bit is at left Number of Samples Image The SAMP image is an integer 16 bit array containing the total number of data samples that were used to compute the corresponding pixel values in the science image For ACCUM and BRIGHTOBJ modes the number of samples contributing to each pixel always has a value of 1 in the raw data file For MULTIACCUM mode the sample values in the raw and intermediate data files are set to the number of readouts that contributed to the corresponding science image NICMOS 2 8 Chapter 2 Data Structures Because the number of samples in the raw images for MULTI ACCUM ACCUM and BRIGHTOB modes is the same value for all pixels of an imset the image array is usually not created to save on data volume and the value of the sample is stored in the header key word PIXVALUE in the SAMP image extension see table 2 4 below ye In MULTIACCUM c
84. 1B 05 870 9 F187N 3 578E 18 4 191 05 7743 F187W 3 193E 19 3 732E 06 816 5 F190N 3 500E 18 4 215E 05 804 7 F204M 5 526E 19 7 637E 06 716 2 F205W 8 599E 20 1 231E 06 703 6 F207M 3 793E 19 5 486E 06 686 8 F212N 2427E 18 3 643E 05 664 7 F215N 2 553E 18 3 932E 05 645 1 F216N 2 327E 18 3 636E 05 605 9 F222M 3 177E 19 5 214E 06 610 4 F237M 2 406E 19 4 507E 06 546 1 POLOL 5 711E 19 7 626E 06 734 1 POL120L 5 639E 19 7 530E 06 734 1 POL240L 5 630E 19 7 51 7TE 06 734 1 SSS a a a A These values have not been recalibrated and are taken from PHOTTAB 17112297n_pht fits NICMOS 5 12 J Chapter 5 Data Analysis Table 5 3 NIC3 Photometric Zeropoints Spectral Element PHOTFLAM PHOTFNU F Vega erg cm A DN Jy sec DN Jy F108N 4 283E 17 1 667E 04 1889 8 F110W 6 143E 19 2 600E 06 1780 2 F113N 3 220E 17 1 368E 04 1771 7 F150W 1 766E 19 1 412E 06 1157 7 F160W 3 125E 19 2 694E 06 1038 9 F164N 6 663E 18 6 021E 05 965 4 F166N 6 793E 18 6 232E 05 1011 2 F175W 8 529E 20 9 590E 07 908 3 F187N 4 679E 18 5 486E 05 7729 F190N 4 306E 18 5 187E 05 804 7 F196N 3 735E 18 4 805E 05 757 3 F200N 3 493E 18 4 649E 05 739 7 F212N 3 008E 18 4 515E 05 664 7 F215N 3 179E 18 4 896E 05 645 1 F222M 3 927E 19 6 446E 06 610 4 F240M 2 161E 19 4 140E 06 534 5 5 3 3 Photometric Corrections Photometric Stability with Time and Temperature The photometric stability of NICMOS was monitored throughout the instrument s lifetime in Cycles 7 and
85. 2 2 1 in the HST Introduc tion For clarity this handbook will use the term extension when refering to a component of a FITS file and the term suffix when referring to the three character identifier in a filename B 1 Rootnames Rootnames of HST data files follow the naming convention defined in table B 1 which expands on the previous convention as follows an initial N indicates a NICMOS exposure an intial O indicates a STIS exposure and the rootnames of files containing association products see below end in a number 0 8 Appendix B Suffixes of Files Common to all Instruments IJ APP B 3 Table B 1 IPPPSSOOT Root File Names Character Meaning I Instrument used will be one of E Engineering data F Fine Guidance Sensors N Near Infrared Camera and Multi Object Spectrograph O Space Telescope Imaging Spectrograph S Engineering subset data T Guide star position data U Wide Field Planetary Camera 2 V High Speed Photometer W Wide Field Planetary Camera X Faint Object Camera Y Faint Object Spectrograph Z Goddard High Resolution Spectrograph PPP Program ID can be any combination of letters or numbers 46 656 combinations possible There is a unique association between program ID and proposal ID ss Observation set ID any combination of letters or numbers 1 296 possible combinations 0 0 Observation ID any combination of letters or numbers 1 296 possible combina
86. 2 22 Chapter 3 Calibration 3 1 3 1 Pipeline Processing OTFR and the HST Archive l 3 1 3 2 NICMOS Calibration Software l a 3 3 3 2 1 The Calibration Pipeline cccccccccccccceeeeeeeeseeeees 3 3 3 2 2 Software for Grism Data Reduction 00008 3 4 3 3 Basic Data Reduction Calnica cccc eee 3 5 3 4 Mosaicing Calnicb cceecceeeeeeeeteeteeeeeeeeee 3 16 3 4 1 Input Files 5 asecns ccs tan tats aden idetei esse baccabettevoacsteens ters 3 17 3 4 2 Output Files cist ieelesetdncustisanvaecceeteorssabsastenseiacanie 3 18 SiS PROCESSING serieei ea ee ieta 3 19 3 5 Recalibration cncisctissasitestaasicncinticansictaainknncaceimans 3 23 3 5 1 Why Recalibrate 0 3 23 3 5 2 Recalibrating the Data ccceeeeeeeeeeeeeeeeeeeeees 3 24 vi Table of Contents Chapter 4 Anomalies and Error SOULCES ooo ccccccsseseeessssssssseesseeeensneeeees 4 1 4 1 NICMOS Dark Current and Bias c cee 4 3 Aled Dark CUnOMIes cosas naiiai a e aa 4 4 4 1 2 Bias Shading and Pedestal 4 5 4 1 3 Dark Reference FileS ccccceceeeeeeeeeeeeeeeeeeeees 4 10 4 1 4 What is Removed by Standard Pipeline ProceSsing ssssseeeeeeneneeeeeeeeeeeees 4 13 4 1 5 Cures How To Get Rid of What s Left 4 13 4 2 BAUS deities hte a eens 4 20 4 3 Detector Nonlinearity ISSUES eee 4 21 4 3 1 New Nonlinearity Calibrations c ee
87. 2 5E 18 1000 0 Calibrated NICMOS data are in units of DN gl so the PHOTFLAM values in their headers are in units of erg em A You can simply multiply these images by the value of PHOTFLAM to obtain fluxes in units of erg cm s Al NICMOS headers also contain the keyword PHOTENU in units of Jy s Multiplying your image by the PHOTFNU value will therefore yield fluxes in Janskys 2 Except for 2 D rectified STIS images which are in units of I Analyzing HST Images If INTRO 3 19 If your HST image contains a source whose flux you know from ground based measurements you may choose to determine the final photometry of your HST image from the counts observed for this source To convert a measured flux F in units of erg cm s AO to an ST magnitude plug it into the following equation m 2 5 x log10 F PHOTZPT where the value of the PHOTZPT keyword is the zero point of the ST magnitude scale The zero point of the ST magnitude system has always been and probably always will be equal to 21 10 a value chosen so that Vega has an ST magnitude of zero for the Johnson V passband see Koornneef et al 1986 Horne 1988 and the Synphot Users Guide synphot The STSDAS synthetic photometry package called synphot can simulate HST observations of astronomical targets with known spectra It contains throughput curves of all HST optical components such as mirrors filters gratings apertures and detectors and can gener
88. 38 5 7 Analysis of Polarization Images 5 43 5 7 1 Introduction vx veri sctesnctcat bento mlecccaciesesrusvarseentermnencess 5 43 BiFa2 TMC ONY crv n atl canada ulna Gerth a 5 44 5 7 3 A Useful Script for Polarization Analysis 5 46 5 8 Grism Data Reduction ccccccceeeteeteeeteees 5 47 5 8 1 Extraction SOMWAME vss ceteoes cous aGecrectniceeesecksestiedadaecied 5 48 52d 2 P FOCESSING a e uaea aeyaeee Ent ien 5 49 viii J Table of Contents Part Ill Appendixes Appendix A IRAF Primer A 1 A 1 Initiating IRAF wistscncscnse Gig atn tease adestsonincntecstantens A 2 A 2 IRAP BASICS irritasies A 4 A 3 Getting IRAF and STSDAS ceeeeeees A 15 Appendix B HST File Nameg B 1 B 1 Rootnames oncisietesderrenscneivsnrcsnsssecnsenciessiactacwaveete res B 2 B 2 Suffixes of Files Common to all IMSIRONMAGINS ices on a Ra B 3 B 3 ASSOCIATIONS e cece eeseeceeeeceeeeeeeteeeeeteetateeeeteeeates B 5 Appendix C Observation Logg C 1 C 1 Observation Log FileS ccceececeeeeeeeteeeeeeeteees C 1 C 2 Retrieving Observation LOGS ccceeeeeees C 9 C 3 Using Observation LOQS cceceeeeeeeee C 10 retace Introduction to Reducing HST Data This data handbook provides an introduction to the process of retrieving and reducing Hubble Space Telescope HST data The reduction procedures calibrations and sources of error specific to each ac
89. 47M ExpT 400 0 s xeyev J 670 501 0 RA Dec 12 20 47 04 12 23 11 7 R G B 6 FITS Header WFPC II DATA DESCRIPTOR KEYWORDS INSTRUME WFPCZ f instrument in use ROOTNAME UZ900103T f rootname of the obsert FILETYPE SCI f shp ext edq sdq sc SCIENCE INSTRUMENT CONFIGURATION MODE FULL instr mode FULL ful SERIALS OFF 7 serial clocks ON OFT IMAGE TYPE CHARACTERISTICS IMAGETYP EXT f DARK BIAS IFLAT UFLAT CDESFILE NO f GENERIC BIAS DARK FLAJ PRTFMT 96 packet format code DATE 27 02 94 date file written dd FILTER CONFIGURATION a Dismiss Puitaing display array RLNN 1 2 3 1 2 4 Getting Data with StarView IJ INTRO 1 9 Marking and Retrieving Data with StarView Datasets are marked for retrieval by first clicking on them then using the Mark button at the top of StarView There is also the All button which will mark all the datasets retrieved in the search Marked datasets will be displayed in the Retrieval window Datasets still within their proprietary period will be displayed in yellow and users other than the proposal PI and those authorized by the PI will not able to retrieve them The release date of files still within their proprietary period will also be indicated on the search results form If satisfied with the marked datasets choose Submit in the Retrieval window to retrieve them You will then be queried for both th
90. 51 0 2279 POL240S 258 72 0 7682 0 7169 0 1311 POL240L 248 18 0 8738 0 9667 0 0673 The resulting coefficient matrices become 0 3936 0 3820 0 0189 0 5187 0 3614 0 1152 My cF 0 4025 0 1166 0 1526 gt Myzc2 0 5250 0 0411 0 3276 0 4054 0 2876 0 1195 0 5159 0 3262 0 3111 which can be used to compute the expected I1 I2 I3 for a given set I Q U By inverting the appropriate matrix the Stokes parameters I Q U can be computed from a set of observations I1 I2 I3 The errors on the Stokes parameters are determined by straightforward propagation of errors 2 2 2 oS o a o a o a I ol I ol I ol where S represents an incoming Stokes vector and defines the set of three observed intensities Therefore o a o a o Ja Ta I 11 L 12 L 13 I 2 2 2 2 2 2 2 2 2 2 2 Z od where aj represents the elements of the inverted transmission coefficients matrix 10 Further detailed information on calibration methodologies and transformations between different polarizers see Mazzuca Sparks Axon NICMOS ISR 98 017 Meth odologies to Calibrating NICMOS Polarimetry Characteristics 1998 NICMOS 5 46 Chapter 5 Data Analysis The Stokes parameters can then be combined to yield the polarized intensity I J Q 0 as well as the degree of polarization P and the position angle of polarization 0p where l fa E Pss T 0 zatang Because the polarizers
91. 5122 Release Date 1995 02 27 02 37 53 Pi qast name Target Name MBF Taryet Description GALAXY ELUPTICAL NUCLEUS 000 Instrument WFPC2 Config WRPC2 OO Start Time 1994 02 26 19 10 17 5 Fla NORMAL U2900101T 12 30 49 tee WYFPC2 hoe eer U2900102T 12 30 49 12 23 28 WFPC2 NORMAL PC1 U2900103T 12 30 49 12 23 28 WFPC2 NORMAL MEP NORMAAL 12 3N 49A 12 23 2R 3 Angle 111 001 sci_fov_config Tabie No Update ed LSH um 9 194deyd W 9 OULNI Getting Data with StarView J INTRO 1 7 Clicking on a given dataset in the Results table will display the information shown in the cells above it Proposal ID Release Date P I etc You may browse through the retrieved datasets either by using the mouse and scroll bar or by using the navigation buttons Scan Previous Next in the top row of mouse buttons The Scan option will automatically step through all of the files retrieved in the search provided that the right most button at the bottom of the Results window is toggled to Update If this button is toggled to No Update the Scan option will go straight to the end of the list of files The ability to obtain a preview is available for many but not all of the datasets in the HDA e g previews are not available for many FOC datasets This is done with the Preview button if it is enabled For images this will display a re sampled ver
92. Calibration Data Searches option will retrieve information on when and where this file was taken and the date after which its use is recommended This will help users decide if they would prefer to recalibrate their data using different files StarView can also be used to search for and view the abstracts of accepted HST proposals Like the Preview capability of StarView this provides additional information about a given dataset and whether it may be useful for your science goals Viewing proposal abstracts is an option under the Searches menu and an example is shown in figure 1 4 The Qualifications window again offers several parameters by which this search can be constrained including proposal I D number HST cycle P I name and combinations thereof In the example shown only the proposal I D number was used Finally StarView can be used during the Phase I proposal process to see whether or not HST observations of a given object or object class have already been made or else are scheduled for execution Specifically the Duplications option under the Searches menu allows users to check a database containing both HDA files and a list of queued observations in order to see if a given object has been or will be observed Similarly under Duplications the user may also query the database of proposal abstracts for a given object or object class to check for archived or scheduled observations Advanced Features of StarView In addition t
93. E FLATDONE UNITDONE PHOTDONE CRIDDONE BACKDONE WARNDONE Correct wrapped pixel values MULTIACCUM zero read signal correction Subtract MULTIACCUM zero read Data quality initialization DQ array Calculate statistical errors ERR array Correct for detectors non linearities Dark correction Bars correction Flat field correction Convert to count rate Populate photometry keywords Identify cosmic ray hits update of DQ arrays in _ima fits output of calnica for MULTIACCUM Calculate background estimates Generate user warnings NICMOS 2 14 JJ Chapter 2 Data Structures Keyword Name Meaning CALSTAGE CAL_VER PROCTIME ILLMCORR ILLMDONE ILLMFILE ILLMPDGR MEAN_BKG PATTERN1 P1_SHAPE P1_PURPS P1_NPTS P1_PSPACE P1_LSPACE P1_ANGLE P1_FRAME P1_ORIENT P1_CENTER BKG_OFF PATTSTEP PATTERN ASN_ID ASN_TAB ASN_MTYP Calibration Status State of the calibration values CALNICA CALNICB UNCALIBRATED Version number of the CALNICA CALNICB code for _cal fits _mos fits files Pipeline processing time MJD Calnicb Calibration Information Subtraction of background illumination pattern reference image input values PERFORM OMIT Subtraction of background illumination pattern reference image output values PERFOMED SKIPPED OMITTED Background illumination pattern reference image filename Background illumination pattern file pedigree Mean background level DN sec computed by calnicb Pattern Keywords P
94. E 3 a ei z J i 4 002 ei SP a a Se nin a Ei 0 100 200 300 seconds seconds To get an idea of pointing stability you can create a jitter ball by plotting jitter along the V2 axis vs jitter along the V3 axis see figure C 5 st gt sgraph x3660102j_jit fits si_v2_avg si_v3_avg Figure C 5 Plotting V2 vs V3 Jitter NOAO IRAF V2 11EXPORT lallo squonk stsci edu Thu 13 52 50 18 Sep 97 squonk stsci edu data squonk1 day118 jitterdata x3y60102j_jit fits a E E A S E E OE A E E S A E A O S E 001 002 g arcsec 003 si_v3_av 004 005 002 1 00E 3 0 001 si_v2_avg arcsec Appendix C Using Observation Logs HJ APP C 15 The tstatistics task can be used to find the mean value of the si_v3_avg column the amount of jitter in arcseconds in the direction of the V3 This value can be used to model jitter in a PSF In this example the mean jitter is 3 mas which is typical for post servicing mission data Figure C 6 Averaging a Column with tstatistics tt gt tstat u26m0801j cmi si_v3_avg u26m0801j cmi si _v3_avg nrows 11 mean stddev median min max 0 003006443888 0 00362533 7 17163E 4 0 00929515 0 00470988 Understanding and interpreting the meaning of the table columns and header keywords is critical to understanding the observation logs Please read the available documentation and contact the STScI Help Desk help stsci edu if you have any questions a
95. ERTURE APER_V2 APER_V3 rit a a R ALTITUDE LOS_SUN LOS_MOON SHADOENT SHADOEXT LOS_SCV LOS_LIMB ol ZODMOD EARTHMOD MOONMOD GALACTIC noua GUIDECMD GUIDEACT GSD_ID GSD_RA GSD_DEC F data conforms to FITS standard INTEGER 4 i 16 2C s 1994 133 06 24 18 35 0 0 0 0 32 32 RA TAN DEC TAN 0 0 0 0 0 0 0 0 WFPC2 z 2 0 2 0 1 134 72 224 72 05233 288 4 102 1 103 NGC3379 PO 1994 133 06 24 18 35 1994 133 06 39 18 35 U2880203 a WFPC2 2 SINGLE 1994 133 06 22 46 91 PN 1 UWFALL 1 565 7 534 593 23 106 08 77 11 1994 133 05 11 29 00 1994 133 05 42 45 00 12 46 58 0 22 3 20 2 35 5 1 0 FINE LOCK z FINE LOCK 0084900235 a 161 70720 12 45407 AS Sy a Se Saag i i i GG SH Ms NS NNNN Se ST Se Si Sia aS bits per data value datatype of the group array number of data axes length of the 1st data axis length of the 2nd data axis image is in group format number of groups number of parameters bits in the parameter block OMS version used to process this observation date time OMS processed observation date times format yyyy ddd hh mm ss ss IMAGE PARAMETERS right ascension of zero jitter pixel deg declination of zero jitter pixel deg x coordinate of zero jitter pixel y coordinate of zero jitter pixe
96. FP SPLIT mode was used the groups will be shifted in wavelength space The independent subintegrations should be coadded prior to analysis RAPID n Each group is a separate subintegration with exposure time given by group parameter EXPOSURE WF PC 1 WF 4 Group n represents CCD chip n e g group 1 is chip 1 unless not all chips were used Group parameter DETECTOR always gives chip used PC 4 Group n is chip n 4 e g group 1 is chip 5 If not all chips were used see the DETECTOR parameter which always gives the chip used WFPC2 All 4 Planetary chip is group 1 detector 1 Wide Field chips are groups 2 4 for detectors 2 4 If not all chips were used see the DETECTOR keyword 2 3 3 Working with GEIS Files This section briefly explains how to work with information in GEIS header and data files GEIS Headers Header keyword information relevant to each group of a GEIS file resides in two places the header file itself and the parameter block associated with the group Because GEIS header files are composed solely of ASCII text they are easy to print using standard Unix or VMS text handling facilities However the group parameters are stored in the binary data file To access them you need to use a task such as imheader as shown in section Printing Header Information You can use the IRAF hedit task to edit the keywords in GEIS headers While it is possible to edit GEIS header files using standard Unix and VMS
97. Fields and a composite quasar spectrum which are also public This chapter describes how to search the HDA how to electronically retrieve files from it and how to request and read tapes and disks containing HST data As an aid to retrieving their data PIs will automatically receive e mail notification of the status of their observations two times first when the first datasets for their proposal are archived and second when all the datasets for their proposal and all necessary calibration files have been archived Note for Advanced Camera for Surveys ACS Users Calibrated ACS images are approximately 168 MB in size larger than those of any other HST instrument Therefore electronic retrieval of ACS data is enabled only for those with broadband gt 100 KB s Internet connec tions in order to ensure uninterrupted transmission of individual files Users retrieving large numbers of ACS files should also consider requesting them on tape or disk 1 1 Archive Overview The HDA contains all HST observations ever made It also contains a database that catalogs and describes these observations There are currently two ways to search and retrieve data from the HDA The first is a program called StarView which acts as an interface to the HDA StarView currently runs as Java based stand alone application that can be downloaded from the web site http starview stsci edu Previous versions of StarView such as XStarView are no longer av
98. I Help Desk at help stsci edu A 3 Getting IRAF and STSDAS Both IRAF and STSDAS are provided free of charge to the astronomical community You must have IRAF to run STSDAS Detailed information about installing and retrieving STSDAS is found in the STSDAS Site Manager s Installation Guide and Reference If you have any problems getting and installing STSDAS TABLES or any other packages or data described in this handbook please contact the Help Desk by sending e mail to help stsci edu A complete description of how to install the synphot data files is provided in section A 3 2 A 3 1 Retrieving the IRAF and STSDAS Software There are three ways to get the software e Use the World Wide Web e Use anonymous FTP e Request a tape World Wide Web The STSDAS World Wide Web page http stsdas stsci edu STSDAS html provides links and instructions for downloading the appropriate files to your local system or to display the software directory from which you can select the series of smaller files Anonymous FTP e IRAF iraf noao edu 140 252 1 1 e STSDAS ftp stsci edu 130 167 1 2 APP A 16 Appendix A Getting IRAF and STSDAS There are two points to remember when using FTP to retrieve STSDAS e You must retrieve and install the TABLES package before STSDAS e You should retrieve the README file from the directory soft ware stsdas v2 0 and read it to find out which files you should retrieve You must have IRAF instal
99. IT PIXVALUE CRPIX1 CRPIX2 CRVAL1 CRVAL2 CD1_1 CD1_2 CD2_1 CD2_2 SAMPNUM SAMPTIME DELTATIM ROUTTIME Meaning Data Description Keywords Name of the extension in an imset of the data file SCI ERR DQ SAMP TIME Extension version integer number to uniquely identify an IMSET in a science data file A MULTI ACCUM file can contain up to 26 IMSETs i e up to EXTVER 26 Switch to allow the image extension header to inherit the primary header keywords Allowed values T TRUE F FALSE Minimum pixel value Maximum pixel value Brightness units allowed values COUNTS COUNTS S When ALL pixels in an image extension have the same value e g the SAMP and TIME arrays in the ima fits file from a MULTIACCUM exposure or the ERR DQ SAMP and TIME arrays in the _raw fits files from a MULTIACCUM ACCUM or BRIGHTOBJ exposure the pixel array of that extension is not generated and the PIX VALUE keyword is instead populated with the common value of the pixels to save space World Coordinate System of Image x coordinate of image s reference pixel y coordinate of image s reference pixel RA of reference pixel degrees DEC of reference pixel degrees Partial derivative of RA with respect to x Partial derivative of RA with respect to y Partial derivative of Dec with respect to x Partial derivative of Dec with respect to y Readout Parameters Sample number of the MULTIACCUM sequence Total integration time sec Integrat
100. It is not sufficient for the table to be just the first BINTABLE or TABLE it must actually be the first extension For example running catfits on the NICMOS association table n3tc01010_ asn fits provides the following output fi gt catfits n3tc01010_asn fits EXT FITSNAME FILENAME EXTVE 0 n3tc01010 asn N3TC01010 ASN FITS 1 BINTABLE ASN Togos Extension number 1 holds the association table which has EXTNAME ASN and EXTVER 1 You can use the tprint task in the STSDAS tables package to print the contents of this table and the following commands are all equivalent tt gt tprint n3tc01010_asn fits tt gt tprint n3tc01010_asn fits 1 tt gt tprint n3tc01010_asn fits asn 1 STSDAS tables tasks can read both FITS TABLE and BINTABLE extensions but they can write tabular results only as BINTABLE extensions Tasks that write to a table in place i e tedit can modify an existing FITS extension and tasks that create a new table i e tcopy will create a new extension when writing to an existing FITS file If the designated output file does not already exist the task will create a new FITS file with the output table in the first extension If the output file already exists your task will append the new table to the end of the existing file the APPEND option necessary for appending FITS image extensions is not required As with FITS images you can specify the EXTNAME and EXTVER of the output extension expl
101. It was designed to implement the potentially complex task of image mosaicing in a pipeline fashion but sometimes a more careful manual treatment can be worthwhile Calnicb does not include any Mosaicing calnicb J NICMOS 3 17 correction for geometric distortion in NICMOS images which is small but may be important for some applications see section 5 4 for a discussion nor does it allow pixel subsampling which may be useful in order to improve image resolution for undersampled images especially with NIC3 Also some NICMOS users dithered their observations manually using POS TARG offsets rather than the canned patterns available in Phase II such data sets will not be linked as associations in the HST archive Finally you may wish to have more interactive control over the various stages of the background subtraction registration and coaddition process than calnicb offers When analyzing NICMOS data you may find it useful to explore other means of combining dithered exposures into a final image mosaic such as the drizzle routine and associated software available in the stsdas analysis dither package see also section 5 4 4 For many applications however calnicb will produce excellent results The HST Dither Handbook Koekemoer et al 2002 provides exten sive information about the software in the stsdas analysis dither pack age The Handbook has many examples showing how to use the drizzling rountines including one fully
102. Load Qualifications Save Qualifications Clear Qualifications Target Resolver Label Qualification click cell to edit Database Field Name Logical Type PI last name sci_pi_last_name lastname Proposal ID w2r_proposid peppropid Target Name m87 sci_targname targetname Radius deqrees 0 10 sci_dec sci_ra radius Dec sci_dec decl RA sci_ra a Results for WFPC2 OTF PI last name FORD Proposal ID 5122 Target Name m87 Release Date 1995 02 27 02 37 53 RA 12 30 49 Dec 12 23 28 Dataset Name U2900101T Filter 1 F658N Serials Mode FULL Shutter A D Gain Filter 2 Exptime 1400 0 Date of Last Software Change calwp2 1994 05 04 00 00 00 0 Date of Last On The Fly Calibration Action Update 2001 09 21 08 04 50 1 SOFTWARE SWITCH REFERENCE FILE OTFRFILE TABLE OTFR ACTION ATODCORR AtoD Correction DBU1405 U R1H PERFORM BLEY CORR Engineering File U2900101T XOH PERFORM BIAS CORR Bias Correction E4P1629BU R2H PERFORM DARKCORR Dark Current FSO1154MU R3H PERFORM FLATCORR Flat Field E391433LU R4H PERFORM ed LSH Buijed 134dey W zZL LO HLNI Figure 1 4 Results of the StarView search for the abstract of Proposal 8725 SSSL Z792 2AE E Load Qualifications Save Qualifications Clear Qualifications Label Qualification click cell to ed Database Field Name Proposal Type type Cycle cycle TAC Panel sci_cat
103. N Such a value will be wrapped to about 26000 DN by the on board difference calculation The BIASCORR step searches for pixel values in the range 23500 to 32768 DN and adds an offset of 65536 DN to these pixel values to reset them to their original real values The BIASCORR step only affects ACCUM and BRIGHTOBJ mode observations although it is applied to all NICMOS data sets For MULTIACCUM data it should have no effect No reference files are used by this step NOISCALC Compute Statistical Errors Errors for MULTIACCUM ACCUM and BRIGHTOBJ modes are computed in the calnica pipeline The NOISCALC step performs the task of computing an estimate of the errors associated with the raw science data based on a noise model for each detector Currently the noise model is a simple combination of detector read noise and Poisson noise in the signal sa ee o2 counts adcgain adcgain where Oq is the read noise in units of electrons adcgain is the analog to digital conversion gain factor in electrons per DN and counts is the signal in a pixel in units of DN Noise is computed in units of electrons but the result is converted to units of DNs for storage in the error image The detector read noise is read pixel by pixel from the NOISFILE reference image and depends on the read rate of the observation fast or slow as well as the number of initial and final reads NREAD Separate NOISFILEs are required for each combination of read r
104. NICMOS 3 15 NICMOS 5 6 NICMOS 6 Index photometry basic in STSDAS INTRO 3 17 differential NICMOS NICMOS 5 13 NICMOS absolute NICMOS 5 17 pixel centering NICMOS NICMOS 5 13 synthetic INTRO 3 19 pipe IRAF task APP A 6 pipeline files produced by INTRO 2 1 NICMOS calibration NICMOS 3 1 pixel bad NICMOS NICMOS 3 9 centering NICMOS NICMOS 5 13 pixel coordinate converting to RA and Dec INTRO 3 10 pixel data GEIS file INTRO 2 16 plot igi task INTRO 3 23 pointing stability APP C 13 polarizer NICMOS NICMOS 1 3 position RA and Dec in STSDAS INTRO 3 10 post calibration association table NICMOS NICMOS 2 3 PostScript psikern IRAF INTRO 3 23 print plots igi INTRO 3 22 proposal comparing to data NICMOS 2 20 PSF NICMOS subtracting NICMOS 5 23 NICMOS variation NICMOS 5 14 psikern PostScript IRAF kernel INTRO 3 23 pstack task plot samples as function of time NICMOS 5 3 R RAMP mode NICMOS NICMOS 1 6 raw science file NICMOS NICMOS 2 2 readout NICMOS mode NICMOS 1 4 recentering jitter APP C 13 red leak NICMOS NICMOS 5 16 resample task flux to wavelength INTRO 3 24 rootname see files naming conventions S SAOimage display image INTRO 3 6 section image INTRO 3 8 sgraph task plot group INTRO 3 20 plot STIS spectra INTRO 3 21 software IRAF APP A 1 APP A 15 STSDAS INTRO 3 1 APP A 15 Space Telescope Science Data Analysis
105. NICMOS group this effect is fondly known as the Mr Staypuft anomaly figure 4 9 Effects of Overexposure J NICMOS 4 35 Figure 4 9 The Mr Staypuft anomaly The bright source at lower right produces electronic ghost images in the other three quadrants plus vertical streaks In Camera 1 images these streaks run horizontally Associated stripe along fast readout direction Electronic Ghosts ae AKA Mr Stay puft Electronic echo of bright source Cures At present there is no real solution to the Mr Staypuft anomaly other than to be aware that such ghost images may exist For example if your image has a bright source at pixel 58 143 then you may see ghost images around 186 143 186 15 and 58 15 If the observation was made with Camera 3 so that the fast clocking direction is along columns there may also be elevated signal at all rows on and around columns 58 and 186 Ordinarily it is not possible to eliminate these ghosts from dithered data by masking since they will move about on the array along with the astronomical targets If for some reason observations were obtained at multiple roll angles then it would be possible to mask the ghosts and eliminate them this was done for the Hubble Deep Field South NICMOS observations Some NICMOS observers studying relatively blank fields have dealt with the elevated columns rows phenomenon by fitting medians to the affected columns rows or to portions of th
106. ORM identify cosmic ray hits BACKCALC PERFORM calculate background estimates WARNCALC PERFORM generate user warnings CALNICA CALIBRATION INDICATORS performed skipped omitted BIASDONE PERFORMED f subtract ADC bias level ZSIGDONE PERFORMED Zero read signal correction ZOFFDONE PERFORMED subtract MULTI ACCUM zero read MASKDONE PERFORMED data quality initialization NOISDONE PERFORMED calculate statistic errors NLINDONE PERFORMED correct for detector nonlinearities DARKDONE PERFORMED dark correction BARSDONE PERFORMED bars correction ki Basic Data Reduction calnica W NICMOS 3 7 Figure 3 2 Calnica Processing Flow Input Processing Keyword Calibrated Files Steps Switches Output Files RAW Science Images MASKFILE NOISFILE DARKFILE NLINFILE Zero Read Signal Correction ZSIGCORR Subtract Zero Read Image ZOFFCORR MASKFILE Mask Bad Pixels MASKCORR Wrapped Pixel Correction BIASCORR NOISFILE DARKFILE Compute Statistical Errors NOISCALC DARKFILE Dark Current Subtraction DARKCORR NLINFILE Linearity Correction NEINCORR Bars Correction BARSCORR FLATFILE Flat Field Correction FLATCORR Convert to Countrates UNITCORR PHOTTAB Photometric Calibration PHOTCALC Cosmic Ray Identification CRIDCALC IMA BACKTAB Predict Background BACKCALG TERR WARNCALC SPT User Warnings NICMOS 3 8 Chapter 3 Calibrat
107. Older instruments FOC FOS FGS GHRS HSP WF PC 1 and WFPC2 generate files in GEIS formats but are stored and delivered as waiver FITS format in the archive and need to be converted back to GEIS format before processing Newer instruments STIS NIC MOS ACS generate and store files in FITS format and should not be converted to GEIS This chapter describes these two HST file formats first giving some historical perspective on the reasons why they were selected then explaining the FITS and GEIS formats in more detail STIS ACS and NICMOS observers should pay particular attention to the section on FITS files which shows how to identify and access the contents of these files and covers some important conventions regarding header keywords Veteran observers with the other instruments will find little new in the section on GEIS files but newcomers to the older HST instruments should consult the material on data groups and conversion from FITS to GEIS before proceeding to chapter 3 of the HST Introduction 2 1 Historical Perspective In the early 1980 s when GEIS was selected as the standard format for HST data files it held several advantages over both FITS and the original IRAF format OIF e GEIS allows floating point data The early incarnations of FITS accommodated only integer data and this restriction to integers would have made data reduction and storage of calibrated data rather cumbersome e GEIS files can h
108. P mode could in principle be used to obtain the benefits of a MULTIACCUM exposure without the large data volume the difficulty of implementing infallible Detector Readout Modes IJ NICMOS 1 7 algorithms for on board processing made this mode impractical and its use for on orbit observations was discouraged in Cycles 7 and 7N Indeed almost no data were obtained in RAMP mode and it will not be supported for NICMOS observing in Cycle 11 and beyond We describe the mode here for historical reasons only but it will not be considered otherwise in this Handbook In RAMP mode the total integration time T is divided into n equal intervals t T n Each readout is differenced on board with the previous readout and used to compute a running mean of the number of counts per sample interval and an associated variance for each pixel Large deviations from the running mean are used to detect saturation or a cosmic ray hit At the end of the exposure the data sent to the ground comprise a mean countrate image plus the variance and the number of valid samples used to compute each pixel value The effective exposure time for the returned image is the sample interval t Almost no data were obtained in RAMP mode during Cycles 7 and 7N and it will not be supported for NICMOS observing in Cycle 11 and beyond The reduction and analysis of RAMP mode data will not be discussed further in this Handbook NICMOS 1 8 W Chapter 1 Instrument Overvi
109. POINTING CONTROL DATA commanded guiding mode actual guiding mode at end of GS acquisition dominant guide star id dominant guide star RA deg dominant guide star DEC deg Appendix C Observation Log Files IJ APP C 7 Figure C 2 Representative jih or cmh Header GSD_MAG 12 867 dominant guide star magnitude GSR_ID 0085201189 roll guide star id GSR_RA 161 93314 roll guide star RA deg GSR_DEC 12 78141 roll guide star DEC deg GSR_MAG 12 977 roll guide star magnitude GSACQ 1994 133 06 31 02 92 actual time of GS acquisition completion PREDGSEP 1420 775 predicted guide star separation arcsec ACTGSSEP 1421 135 actual guide star separation arcsec GSSEPRMS 3 8 RMS of guide star separation milli arcsec NLOSSES 0 number of loss of lock events LOCKLOSS 0 0 total loss of lock time sec NRECENT 0 number of recentering events RECENTR 0 0 total recentering time sec LINE OF SIGHT JITTER SUMMARY V2_RMS 4 5 V2 axis RMS milli arcsec V2_P2P 51 6 V2 axis peak to peak milli arcsec V3_RMS 20 9 V3 axis RMS milli arcsec V3_P2P 267 3 V3 axis peak to peak milli arcsec RA_AVG 161 85226 average RA deg DEC_AVG 12 58265 average dec deg ROLL_AVG 293 01558 average roll deg PROBLEM FLAGS WARNINGS and STATUS MESSAGES present only if problem exists ACQ2FAIL T target acquisition failure GSFAIL DEGRADED guide star acquisition failure
110. Preface Future changes in this handbook are anticipated as MAST expands to cover additional missions and as StarView and PyRAF evolve The reader is advised to consult the STScI web site at http resources stsci edu for the latest information Moreover as the present revision comes before SM3B important revisions to the ACS file structure and data handling may be necessary after the installation of this instrument Bahram Mobasher Chief Editor HST Data Handbook Michael Corbin Editor Chapter 1 Jin chung Hsu Editor Chapters 2 and 3 PART Introduction to Reducing HST Data This part of the data handbook provides an introduction to the process of retrieving and reducing Hubble Space Telescope HST data Hi Part I Introduction to Reducing HST Data CHAPTER 1 Getting HST Data In this chapter 1 1 Archive Overview 1 2 1 2 Getting Data with StarView 1 4 1 3 Getting Data With the World Wide Web 1 16 1 4 Reading HST Data Tapes and Disks 1 17 This chapter describes how to obtain Hubble Space Telescope HST data files All HST data files are stored in the Hubble Data Archive HDA which forms part of the Multimission Archive at STScI MAST HST Guaranteed Time Observers GTOs Guest Observers GOs and Archival Researchers can retrieve data in either of two ways e Electronically over the Internet from the HDA where data are stored immediately after they pass through HST pipeline processing
111. Preparing FOS and GHRS Data eee 3 24 3 5 2 Preparing STIS Spectra for Analysis 0 0 3 27 3 5 3 General Tasks for Spectra ccccceccccceeceeeeeeeeeeeees 3 30 3 5 4 STSDAS fitting Package 3 34 3 0 D SPOCM aiani eae a ee ae en 3 37 3 0 FRETCFENCES nrus tie aeii 3 37 3 6 1 Available from STSCI eccceeceeeeeeeeeeseeeeeeeeeeeeaes 3 37 3 6 2 Available from NOAO nsee 3 38 3 6 3 Other References Cited in This Chapter 3 38 Table of Contents W v Part Il NICMOS Data Handbook NICMOS Introduction 000 00 1 Chapter 1 Instrument Overview 1 1 1 1 Instrument Overview scssi 1 1 1 2 Detector Readout Modes ccccccceeeeeeteeeee 1 4 eT IO GAC Me acessndas nctesktuicaseizvameneasbatieevanedanasteuntss 1 5 T22 FAG GUI dass nl tah a E aa A eee eeeesecress 1 5 t23 BRIGHTOB SD vear i eta Aa 1 6 1 2 4 RAMP edhe uleicrrenchealude rat meu esas bok Mates 1 6 Chapter 2 Data Structures 2 1 2 1 NICMOS Data Files 1 00 2 1 2 1 1 File Name SUTTIKES xscsuiiscicseesardenetassaecdenindns 2 2 2 1 2 Science Dalal Files invisi 2 3 2 1 3 Auxiliary Data Files nnnnsnnnnnnnnannnneseenerrnrrrrrreesss 2 9 2 2 Header KOywords ccccececceeceeeceeesseeeeeeeeeee 2 10 2 3 Working with NICMOS Files ceeeee 2 16 2 4 From the Phase II Proposal to Your Data 2 20 2 5 Paper Products sisicessesisesl csinnni waliieinan alas
112. RAF If you are not already familiar with IRAF consult the IRAF Primer in Appendix A before reading further INTRO 3 1 INTRO 3 2 J Chapter 3 STSDAS Basics 3 1 Navigating STSDAS 3 1 1 3 1 2 The tasks in STSDAS are far too numerous and complicated to describe comprehensively in this volume Instead we will show you where to find the STSDAS tasks appropriate for handling certain jobs You can refer to online help or the STSDAS User s Guide for details on how to use these tasks Some useful online help commands are e help task provides detailed descriptions and examples of each task e help package lists the tasks in a given package and their functions e describe task provides a detailed description of each task e example task provides examples of each task apropos word searches the online help database for tasks relating to the specified word see figure A 4 STSDAS Structure STSDAS is structured so that related tasks are grouped together as packages For example tasks used in the calibration process can be found in the hst_calib package and tasks used for image display and plotting can be found in the graphics pack Figure 3 1 shows the STSDAS package structure Note that IRAF version 2 11 must be installed on your system in order for you to use STSDAS 2 0 and TABLES version 2 0 or higher Packages of General Interest Images Both IRAF and STSDAS contain a large number of tasks that work with HST images
113. RAF prompt such as st gt shows the first two letters of the most recently loaded package The fitsio package contains the STSDAS programs called tasks in the IRAF STSDAS environment required to read and write FITS files to and from tapes and disks The two principle tasks are strfits for reading files and stwfits for writing them Next set the IRAF environment variable imtype to specify that your data files are to be written in GEIS format This is done by typing fi gt set imtype hhh You should then move to the directory containing the FITS files The last step is to use strfits to read the data Like most IRAF STSDAS tasks strfits has several parameters that control its function You can either edit these tasks using the IRAF epar command or specify them on the command line For the purpose converting FITS files to GEIS files the important parameter is oldirafname which needs to be set to yes in order to keep the file rootname the same To convert all the FITS files in a directory to GEIS files type fi gt strfits fits oldirafname yes Reading HST Data Tapes and Disks IJ INTRO 1 19 Figure 1 6 MAST Home Page rl Netscape MAST File Edit View Go Communicator Back Forward Reload Home Search Netscape Print Secunty Shop Stop lt 3 a 2 a O FF a Bookmarks Aj Location http archive stsci edu z What s Relatec febilai adio eople ellow Pages ownloa ale
114. RSDONE FLATDONE UNITDONE PHOTDONE CRIDDONE BACKDONE WARNDONE NICMOS 2 18 J Chapter 2 Data Structures The entire suite of keywords from any header can be listed with the IRAF task imheader Given that NICMOS data files contain multiple extensions the number of the desired extension must always be specified For example to list the primary header content of a calibrated image you type cl gt imheader n0g70106t_cal fits 0 long page where 0 identifies the primary header To list the header of the second science image ina MULTIACCUM sequence the sixth extension cl gt imheader n0g70106t_cal fits 6 long page Chapter 2 of the HST Introduction describes in detail how to work with FITS file extensions Here we will recap the essentials In order to simplify access to NICMOS FITS image extensions each extension header contains the two keywords EXTNAME extension name and EXTVER extension version number The EXTNAME keyword identifies the nature of the extension SCI ERR DQ SAMP TIME see table 2 7 The EXTVER keyword contains an integer value which is used to uniquely identify a particular imset quintuple of image extensions For example the five image extensions single imset contained in the science data file for an ACCUM or BRIGHTOBJ observation will all usually be assigned an EXTVER value of 1 because there will only be one set of extensions in the file In a MULTIACCUM science data file each
115. S Flexible Image Transport System format You should thus first create a directory where you want your data to reside e g home myname myhstdata go to that directory then read the tape or disk using the Unix Linux tar command to read the FITS files into it Currently datasets obtained with HST s original instruments FGS FOC FOS GHRS HSP and WFPC as well as WFPC2 must have their FITS files converted to GEIS Generic Edited Information Set format in order to work on them with IRAF STSDAS Further information on HST file formats is presented in chapter 2 STSDAS is the package analysis software for HST data and is discussed further in chapter 3 Datasets obtained with the other current HST instruments ACS NICMOS and STIS should be reduced in FITS format without conversion to GEIS STSDAS support for the analysis of WFPC2 data in FITS format is currently planned The steps for reading and converting FITS files to GEIS files are as follows First bring up IRAF STSDAS in your IRAF home directory by typing gt cl 4 A description of FITS format and various supporting documents can be found at the Web site http fits gsfc nasa gov fits_home html INTRO 1 18 Chapter 1 Getting HST Data This will start an IRAF session IRAF and STSDAS are organized into packages To load a package type its name To begin with you must load the stsdas and fitsio FITS Input Output packages cl gt stsdas st gt fitsio The I
116. S Safed WFII Safing This observation affected when WFII Safed FOC Safing This observation affected when FOC Safed Shut FOS aperture door is not Open FAILED FGS astrometry target acquisition failed APP C 8 Appendix C Observation Log Files Table C 3 Contents of jit or cmiTable Three Second Averaging Parameter Units Description seconds seconds Time since window start v2 dom arcseconds Dominant FGS V2 coordinate V3 dom arcseconds Dominant FGS V3 coordinate v2 roll arcseconds Roll FGS V2 coordinate v3 roll arcseconds Roll FGS V3 coordinate SI V2 AVG arcseconds Mean jitter in 3 seconds SI V2 RMS arcseconds rms jitter in 3 seconds SI V2 P2P arcseconds Peak jitter in 3 seconds SI V3 AVG arcseconds Mean jitter in 3 seconds SI V3 RMS arcseconds rms jitter in 3 seconds SI V3 P2P arcseconds Peak jitter in 3 seconds RA degrees Right ascension of aperture reference DEC degrees Declination of aperture reference Roll degrees Angle between North and V3 LimbAng degrees Angle between earth limb and target TermAng degrees Angle between terminator and target LOS Zenith degrees Angle between HST zenith and target Latitude degrees HST subpoint latitude Longitude degrees HST subpoint longitude Mag V1 V2 V3 degrees Magnetic field along V1 V2 V3 EarthMod V Mag arcsec Model earth background light SI_Specific Special science instrument data DayNight 0 1 flag Day 0 or night 1 Recent
117. S dataset File Name Suffixes Each file in a NICMOS dataset has a three character suffix that uniquely identifies the file contents The file name suffixes for NICMOS and the corresponding file contents are summarized below The files that contain final calibrated data which you will most likely use for analysis are highlighted in bold italics and are _cal and _mos for unassociated and associated data respectively This list contains all of the files that the pipeline can produce For some observing strategies not all of the processing steps are performed and only a subset of these files will be produced by the pipeline e Raw Data Files Raw Science File _raw This FITS file contains the raw image data received from the spacecraft One file per exposure is created a MULTIACCUM exposure is considered a single exposure irrespective of the num ber of samples specified Support File _spt This FITS file contains supporting information about the observa tion the spacecraft telemetry and engineering data from the instru ment that was recorded at the time of the observation including detector temperature measurements Association Table _asn This file is a FITS binary table that contains the list of datasets making up an association e Calibrated Data Files Calibrated Science File _cal This FITS file contains the calibrated science data for an individ ual dataset and is produced by the pipeline calibration task
118. SPARS256 can cool between the first and last reads resulting in a NICMOS Dark Current and Bias IJ NICMOS 4 7 DELTATIME 256s shading that is different in the 25 read than it was in the 4 read A similar situation occurs in the MIF sequences when the DELTATIMEs switch over from the relatively long steps in the middle to the rapid reads at the end the first short read of the set taken at the end of the observation has slightly different shading than the remaining short reads or the initial short reads Numerically shading is of the form S x y s dt x y T where the shading s is a function of the pixel location DELTATIME dt and detector temperature T Images of the shading as a function of DELTATIME and temperature can be made by subtracting the amp glow and linear dark components from DARK observations These images can then be used to build dark reference files for any sequence given a set of DELTATIMEs and a temperature The shading patterns of the NICMOS cameras were measured using data taken early in the Cycle 7 calibration program and the synthetic dark reference files used in the standard STScI pipeline processing use these shading images taken with the detectors at 61 4 K in the fall of 1997 However as the instrument was monitored over the course of many months the temperature dependence was discovered Because the temperature varied during the lifetime of the instrument so did the shading This variation is not yet t
119. STSDAS tasks other than the sgraph task and the igi package which have been appropriately modified you will need to extract the desired arrays from the three dimensional table Two new IRAF tasks named tximage and txtable can be used to extract the table cell arrays Complementary tasks named tiimage and titable will insert arrays back into table cells To specify the arrays which should be extracted from or inserted into the table cells you will need to use the selectors syntax to specify the desired row and column The general syntax for selecting a particular cell is intable fits extension number c column_selector r row_selector or intable fits keyword options c column_selector x row_selector A column selector is a list of column patterns separated by commas The column pattern is either a column name a file name containing a list of column names or a pattern using the IRAF pattern matching syntax type help system match for a description of the IRAF pattern matching syntax If you need a list of the column names you can run the tlcol task type tlcol infile fits INTRO 2 12 Chapter 2 HST File Formats Rows are selected according to a filter The filter is evaluated at each table row and the row is selected if the filter is true For example if you specify infile fits 3 c WAVELENGTH FLUX r SPORDER 68 70 IRAF will extract data from the table stored in the third extension of t
120. Submit in the window that will be spawned by marking the files 9 Enter your MAST username and password and specify the means of data delivery StarView remembers your name and password from past searches so it does not have to be entered each time 10 Click Done and your data are on their way You will receive an e mail message when your retrieval has been queued and another when the transfer is complete 1 3 Getting Data With the World Wide Web HDA datasets can be searched for previewed and retrieved via the World Wide Web in very much the same way as with StarView As noted in section 1 1 StarView offers more capabilities for this process including cross qualification the use of VTT and more information about instrument calibration files However Web retrievals may be preferable in some cases particularly when information on calibration files is not needed and the hypertext on the Results pages makes it easy to access all the information they contain The starting point for Web based searches of the HDA is the MAST web site at http archive stsci edu gt This web page is shown in figure 1 6 A powerful feature of MAST is that all of its mission archives including the HDA can be searched simultaneously This is done with the Cross Correlation Target Search option shown on the MAST home page This search will return all datasets for all missions available for a given object or coordinates according to the search const
121. TS format While other FITS readers may be able to read portions of the data correctly they are unlikely to reconstruct the entire data file properly To recreate the original multigroup GEIS file using strfits you must first type cl gt set imtype hhh INTRO 2 14 Chapter 2 HST File Formats 2 3 2 This command tells IRAF to write output files in GEIS format You then need to set the strfits parameters xdimtogf and oldirafname both to ves For example after you have set imt ype hhh you can convert the FITS file _hhf f its into the GEIS format files hhh and hhd by typing cl gt strfits hhf fits xdim yes oldiraf yes GEIS Data Groups One of the original advantages of GEIS format noted in Section 2 1 was that it could accommodate multiple images within a single file This feature is useful because a single HST observation often produces multiple images or spectra For example a single WF PC 1 or WFPC2 exposure generates four simultaneous images one for each CCD chip Likewise the FOS and GHRS obtain data in a time resolved fashion so that a single FOS or GHRS dataset comprises many spectra one corresponding to each readout The data corresponding to each sub image for the WF PC 1 or WFPC2 or each sub integration for the FOS or GHRS are stored sequentially in the groups of a single GEIS binary data file The header file corresponding to this data file contains the information
122. TSDAS packages and tasks for performing photometry on HST images apphot aperture photometry package daophot stellar photometry package useful for crowded fields isophote package for fitting elliptical isophotes imexamine performs simple photometry measurements imstat computes image pixel statistics imcnts sums counts over a specified region subtracting background plcreate creates pixel masks Consult the online help for more details on these tasks and packages The document Photometry using IRAF by Lisa A Wells provides a general guide to performing photometry with IRAF it is available through the IRAF web page http iraf noao edu docs photom html The apphot package allows you to measure fluxes within a series of concentric apertures This technique can be used to determine the flux in the wings of the PSF which is useful if you wish to estimate the flux of a saturated star by scaling the flux in the wings of the PSF to an unsaturated PSF INTRO 3 18 Chapter 3 STSDAS Basics Converting Counts to Flux or Magnitude All calibrated HST images record signal in units of counts or Data Numbers DN NICMOS data is DN s The pipeline calibration tasks do not alter the units of the pixels in the image Instead they calculate and write the inverse sensitivity conversion factor PHOTFLAM and the ST magnitude scale zero point PHOTZPT into header keywords in the calibrated data WF PC 1 and WFPC2 obser
123. TSDAS ttools package reads a GEIS format spectral image and writes the list of data values to a column of an STSDAS table creating a new output table if necessary The following example shows how to create a flux wavelength and error table from group eight of a GEIS format FOS dataset cl gt imtab yOcy0108t cOh 8 yOcy0108t tab wavelength cl gt imtab yOcy0108t clh 8 yOcy0108t tab flux cl gt imtab yOcy0108t c2h 8 yOcy0108t tab error The last word on each command line labels the three columns wavelength flux and error 3 5 2 Analyzing HST Spectra W INTRO 3 27 Constructing tables is necessary if you plan to use certain tasks such as those in the STSDAS fitting package that do not currently recognize the multispec format WCS header information Tabulating your spectra is also the best option if you want to join two or more spectra taken with different gratings into a single spectrum covering the complete wavelength range Because the data are stored as individual wavelength flux pairs you do not need to resample and therefore degrade the individual spectra to a common linear dispersion scale before joining them Instead you could create separate tables for spectra from different gratings and then combine the two tables using for example the tmerge task cl gt tmerge n5548 h13 tab n5548 h19 tab n5548 tab append Note that you will first have to edit out any regions of overlapping wavelength from one
124. The position of the coronagraphic hole can then be inferred by subtracting the offset slew and the coronagraphic hole offset from the position of the target NXHOLE 122 726 78 914 0 25 43 562 NYHOLE 80 683 103 718 0 75 183 651 A fix was included in OPUS 9 2 which was installed July 16 1998 The slew and target position keywords NXCENTP NYCENTP NOFF STXP and NOFFSTYP were added to the SPT file These keyword val ues are in detector coordinates The IMAGE coordinate system for NICMOS Cameras 1 2 3 have been defined such that the origin will be in the lower left hand corner when displayed while DETECTOR coordinates are defined by the readout directions for each camera Any NICMOS camera image when displayed using the IRAF display command will be displayed relative to the HST field of view as depicted in the NICMOS Instrument Handbook The conversion from DETECTOR coordinates to IMAGE coordinates is performed during OPUS pipeline processing For Camera 2 the OPUS x direction is detector y direction and correspondingly the OPUS y direction is detector x direction Care must be exercised when converting from one coordinate system to the other NICMOS 5 34 Chapter 5 Data Analysis Measuring the Hole Position The coronagraphic hole location can be determined from off line processed ACQ images and should be very close to the inferred location of the hole determined by subtracting the FSW slew from t
125. W and F175W should be used with caution These bandpasses are so broad that the conversion from source flux to count rate will be very strongly dependent on the color or spectrum of the source The photometric calibration information presented here is appropriate for NICMOS data taken during Cycles 7 and 7N only In Cycle 11 and thereafter NICMOS will most likely be operating at a significantly warmer temperature regulated by the NICMOS Cooling System Because the detector quantum efficiency is a function of temperature the photometric zeropoint calibrations will almost certainly be differ ent than those appropriate to Cycle 7 data New photometric calibra tions will be derived as quickly as possible in Cycle 11 Please check the STScI NICMOS web pages for updates on photometric calibration for Cycle 11 data In the header of calibrated NICMOS images there are three additional photometric parameters that characterize the filter used for the observation PHOTPLAM and PHOTBW and provide the ST magnitude zero point PHOTZPT PHOTPLAM gives the value of the pivot wavelength of the filter in Angstroms This wavelength is source independent and is the wavelength for which PHOTFLAM cx PHOTFNUx PHOTPLAM where c is the speed of light in vacuum PHOTBW gives the rms band width of the filter in A see the Synphot User s Guide for a detailed definition of both parameters The magnitude of an object can be determined in the ST syst
126. a The error estimate e for each pixel is taken from the ERR array of the input grism image The error estimate e for each wavelength is then the weighted quadratic sum over the errors of all pixels at constant wavelength Wavelength Calibration The dispersion relation and the deviation of the spectra have been determined from wavelength calibration observations and are parametrized as 2 3 a 4 X ayx a x where x is the deflection in pixels relative to the position of the object in the direct image and A is the corresponding wavelength The coefficients are contained in the reference file grismspec dat The dispersion relation is given by Ay b birt br 5 7 where r is the distance of a pixel x y from the object of coordinates x y and Ay is the deviation in pixels of the spectrum from a horizontal line The alignment of the spectrum is taken into account by rotating the grism image around the object position xo Y prior to the extraction The distortions in the spectra are taken into account by introducing a corresponding distortion in the weights used for the extraction Flatfielding of Spectra After the spectra are extracted the fluxes are corrected for pixel to pixel variations in the quantum efficiency of the detector i e flatfielded The NICMOS 5 52 Chapter 5 Data Analysis QE variations depend both on the wavelength and on the position of the object on the detector Because of thi
127. a Handbook is based on experience with NICMOS data obtained during the first two years of operation i e HST Cycles 7 and 7N before cryogen exhaustion It is expected that instrument performance may be somewhat different in Cycle 11 wW and beyond with the NICMOS Cooling System and that some aspects of NICMOS data reduction will accordingly require revision NIC MOS users should carefully monitor developments and updates posted on the STScI NICMOS web pages when analyzing data taken in Cycle 11 and beyond NICMOS provides imaging capabilities in broad medium and narrow band filters broad band imaging polarimetry coronographic imaging and slitless grism spectroscopy in the wavelength range 0 8 2 5 um NICMOS is an axial instrument and has three adjacent but not contiguous cameras designed to operate independently and simultaneously Each camera has a different magnification scale and is equipped with a dedicated 256 x 256 HgCdTe Rockwell array The approximate pixel sizes and fields of view are 0 043 and 11 x 11 for Camera 1 referred to as NIC1 0 075 and 19 2 x 19 2 for NIC2 and 0 2 and 51 2 x 51 2 for NIC3 Each camera is provided with its own set of filters mounted on three independent wheels There are a total of 20 filter positions on each wheel 2 To subscribe to the STAN send a message to majordomo stsci edu with the Sub ject line blank and subscribe nicmos_news in the body Instr
128. a floating point image in units of DNs per second count rates Error Image The error image is a floating point array containing an estimate of the statistical uncertainty associated with each corresponding science image pixel This image is computed in the ground calibration pipeline task calnica as a combination of detector read noise and Poisson noise in the accumulated science image counts see chapter 3 and is expressed in terms of lo uncertainties For calibrated MULTIACCUM images ie cal fits files the values of the error array are computed uncertainties in the count rates derived from the linear fit to counts vs exposure time from the intermediate readouts NICMOS Data Files HJ NICMOS 2 7 Data Quality Image This integer unsigned 16 bit array contains bit encoded data quality flags indicating various status and problem conditions associated with corresponding pixels in the science image Because the flag values are bit encoded a total of 16 simultaneous conditions can be associated with each pixel Table 2 2 lists the flag values and their meanings Table 2 2 NICMOS Data Flag Values Flag Value Bit Setting Flag Meaning 0 0000 0000 0000 0000 No known problems 1 0000 0000 0000 0001 Reed Solomon decoding error in telemetry 2 0000 0000 0000 0010 Poor or uncertain Linearity correction 4 0000 0000 0000 0100 Poor or uncertain Dark correction 8 0000 0000 0000 1000 Poor or uncertain Flat Field correction 16 0000 0000 0001 0
129. a level of several percent setting a fundamental limit on the accuracy of any absolute flux calibration in the near infrared including that of NICMOS In the case of NICMOS the photometric calibration is based on observations of solar analogs and hydrogen white dwarfs WDs The stars P330E solar analog and G191B2B WD define the primary calibration with a few other stars observed as cross checks Bohlin Dickinson amp Calzetti 2001 have recently recalibrated the absolute flux density distribution of the HST NICMOS standards The optical and UV portions of their spectra were measured with high quality HST STIS observations which were then carefully matched to stellar atmosphere models for extrapolation to near infrared wavelengths The infrared extrapolations were then checked by comparison to the most up to date ground based broad band photometry for these stars normalized to flux density using the Campins et al 1985 calibrations adjusted for small bandpass differences The STScI NICMOS group and NICMOS IDT have recently reanalyzed all photometric calibration data taken in orbit with NICMOS during Cycles 7 and 7N Unlike earlier efforts the new work uses a larger number of measurements applies uniform and up to date NICMOS calibration software and reference files and employs a more careful treatment of the NICMOS photometric aperture corrections than was used for the original calibration effort Table 5 1 through table 5 3 give t
130. a parameter epar will usually display an error message saying something like Parameter Value is Out of Range The message is displayed when you move to another parameter or if you press Return Table A 1 lists the different parameter types Appendix A IRAF Basics J APP A 11 Table A 1 Parameter Data Types Description Full name of the file Wild card characters and are often allowed Some tasks allow you to use special features when specifying file names including lists IRAF networking syntax and image section or group syntax See File Manage ment below Whole number Often the task will specify minimum or maxi mum values see the help pages Floating point numbers can be expressed in exponential nota tion Often will have minimum and maximum values Logical yes or no values Any characters Sometimes file names are specified as string Parameter set Restoring Parameter Default Values Occasionally IRAF or you will get confused by your parameter values To alleviate this confusion you can restore the default parameters with the unlearn command You can use unlearn on either a task or on an entire package The unlearn command generally will restore the parameters to reason able values a big help if you are no longer sure which parameter val ues you have changed in a complicated task A 2 5 Setting Environment Variables IRAF uses environment variables
131. a sigma sigma sigma Fi87W F187N Fi60W F187N Fi10W F187W focus variation 0 62 1 86 6 81 17 29 cold mask wiggling 0 10 3 15 14 38 37 67 color dependence 23 50 0 58 8000K 3000K 8 91 1 57 color dependence 1 52 8000K 6000K 1 32 color dependence 25 31 6000K 3000K 7 32 The effects of both cold mask wiggling and focus breathing introduce errors in a PSF subtracted image well above 20 of the PSF signal in a narrow band filter with a spatial scale of a few pixels The main effect of PSF color dependence is adding a systemic component to the PSF subtracted image The effect is quite large if the color of the PSF used for subtraction is very different from the image PSF color It is pronounced in blue wide filters like F110W while in filters like FI87W or redder narrower it is essentially negligible The best way to cope with this effect is to use PSFs with colors well matched to the sources PSF subtraction with NICMOS Camera 3 is extremely difficult due to the large pixel scale which severely undersamples the point spread function and because of the strong intrapixel sensitivity variations see section 5 3 3 which affect the structure of point source images NICMOS 5 26 Chapter 5 Data Analysis Figure 5 4 Effect of cold mask wiggling on PSF subtraction in broad band and narrow band filters Left panels normalized counts log scale in the central col umn of the two TinyTim PSFs with 0 005 difference of the col
132. a taken with other instruments such as WFPC2 it may be important to take the effect into account This can easily be done when drizzling NICMOS images using the coefficient matrices presented below Geometric Distortion The distortion corrections for the NICMOS cameras are small but for precision astrometry or when registering and coadding images especially taken with a wide dither pattern or when assembling mosaics covering a large field it should be taken into account The geometric distortion was measured using dithered observations of the astrometric field NGC1850 through all three cameras The data analysis and results are described in detail in an instrument science report ISR by Cox et al 1997 ISR OSG CAL 97 07 As noted in that report the original observations were made in May 1997 when NICMOS Camera 3 was not in perfect focus which can only be achieved during special campaigns when the telescope secondary is moved This together with field vignetting means that the Camera 3 distortion solution from the Cox et al ISR is not as well determined as that for Cameras 1 and 2 The geometric distortion correction for Camera 3 was rederived later using a reobservation made during the January 1998 refocus campaign the Field Offset Mirror FOM 3 Please note that these scale ratios may not agree precisely with the values reported in the NICMOS pixel scale records described above This is because they are defined and derived in a
133. absolute spectrophotometry NICMOS NICMOS 5 18 NICMOSlook program NICMOS 3 4 spectroscopy NICMOS NICMOS 3 4 group number in image INTRO 2 14 working with INTRO 3 8 grspec task plot groups INTRO 3 21 guidance mode observation log APP C 10 guide stars acquisition APP C 10 acquisition failure APP C 11 dominant roll APP C 10 number used APP C 10 H hardcopy see print or paper products header file GEIS INTRO 2 15 keyword inheritance in FITS INTRO 2 7 NICMOS keywords NICMOS 2 10 header data unit FITS file INTRO 2 3 help STSDAS and IRAF tasks INTRO 3 2 APP A 7 l igi plotting with INTRO 3 23 printing plots INTRO 3 22 NICMOS 4 Index image display INTRO 3 4 INTRO 3 5 GEIS file INTRO 2 16 plot data implot INTRO 3 12 section INTRO 3 8 see also FITS STSDAS tasks INTRO 3 2 working with INTRO 3 2 Image Reduction and Analysis Facility see IRAF image set see imset imcopy task FITS files INTRO 2 8 imexamine task image display and plot INTRO 3 13 imgtools package multigroup GEIS images INTRO 3 2 imheader task examine NICMOS header NICMOS 2 18 iminfo task examine NICMOS header NICMOS 2 16 implot task plot image data INTRO 3 12 imset combination msjoin task INTRO 3 16 extraction mssplit task INTRO 3 16 statistics msstatistics task INTRO 3 16 STSDAS tasks for INTRO 3 14 imtab task header to table INTRO 3 26 integration NICMOS NICMOS
134. ach IMSET readout of a MULTIACCUM image is the cumulative sum of the total exposure time prior to that readout As such the sci images are not statistically independent When analyzing NICMOS images it is sometimes helpful to look at the data which was collected during each readout interval independent of that which was accumulated previously i e by taking the difference of successive readouts In this way you can isolate readouts with problems e g major cosmic ray hits or moving objects sudden changes in bias scattered light etc The sampdiff task automates this process Note that in general this is only really a sensible thing to do if the image has not been converted from counts to count rate by the UNITCORR step of calnica The sampcum task inverts this process re accumulating the first differences Using These Tasks An Example As an example you might want to inspect NICMOS data for anomalies which occur during individual readouts during a MULTIACCUM using a procedure like this ni gt nicpipe n4xjl3jwq_raw fits stage biaseq ni gt sampdiff n4xj1l3jwq_ima fits n4xjl3jwq_ fdiff fits ni gt mosdisplay n4xj1l3jwq_fdiff fits 1 extname sci number ni gt pstats n4xjl3jwq_fdiff fits 1 128 1 128 gt gt gt extname sci units rate stat midpt In this example the raw image is first partially processed through calnica using nicpipe By setting stage biaseq the pipeline processing stops before flatfieldi
135. acy in order to achieve good results The IRAF task xregister provides one way to determine the offsets between the images and to shift one into alignment with the other For the example considered here a 995 pixel region 27 121 162 256 around the hole was used as the area for cross correlation and a shift of dx 0 286 dy 0 136 pixels was measured between the images The example shown in figure 5 8 and figure 5 9 displays the subtraction of the two images using both unregistered left and registered right data The subtraction using the registered images exhibits a more symmetrical residual light pattern about the hole Occasionally cross correlation does not yield the best measure of the image offsets You may find that trial and error shifting by various fractional pixel amounts minimizing the subtraction residuals by eye can yield the best results 7 NICMOS Instrument Science Report NICMOS ISR 98 012 NICMOS 5 42 Chapter 5 Data Analysis Figure 5 8 PSF Subtraction F110W filter images obtained in back to back orbits with a roll of the spacecraft between orbits Direct subtraction of images left and a subtraction with the second image shifted to match the first image right orbit 4 5 orbit 4 5 unregistered registered Gaussian Convolution The interpolation introduced by sub pixel shifting has the effect of smoothing the image slightly Subtracting the blurred image from the unblurred image ha
136. ag the cosmic ray affected pixels manually before CRIDCALC processing First partially process the images through calnica excluding the CRIDCALC stage i e setting CRIDCALC to OMIT Next in the resulting _ima fits image edit the DQ extension of the first IMSET affected by the cosmic ray setting the affected pixels to the cosmic ray flag value 512 see table 2 2 Finally set CRIDCALC to PERFORM in the _ima fits file and complete the calnica processing using the modified _ima fits as input The technique described here for flagging monster cosmic rays can also be used to flag and eliminate trails from moving targets usually space junk which occasionally cross through NICMOS images Scattered Earthlight IJ NICMOS 4 39 4 8 Scattered Earthlight All HST instruments are occasionally subject to scattered earthlight which enters when the telescope is pointing near the bright earth limb This results in an elevated background level which does not necessarily illuminate the detector in the same way as the sky does and thus does not flatfield away properly For NICMOS MULTIACCUM observations scattered light during a portion of the exposure usually either the beginning or the end will also cause the signal level to accumulate in a non linear way with time i e either with an initial or final ramp up where the scattered light elevates the count rate for some of the readouts This can cause problems when the calnica CRIDCALC routine
137. ages works only with showall set Space Telescope Science Data Analysis System Space Telescope Science Institute Baltimore Maryland For help send e mail to hotseat stsci edu STSDAS STSDAS Version 1 3 21 September 1993 or phone 410 516 5100 describe fitsio hst_calib problems stlocal examples graphics playpen sobsolete toolbox Some helpful commands for managing packages are e Lists tasks in the most recently loaded package e Lists all tasks loaded regardless of package e package Lists names of all loaded packages e bye Exits the current package APP A 6 lf Appendix A IRAF Basics A 2 2 Running Tasks This section explains how to run tasks background tasks and system level commands and how to use piping and redirection Running a Task The simplest way to run a task is to type its name or any unambiguous abbreviation of it The task will then prompt you for the values of any required parameters such as the names of input files Alternatively you can specify the values for the required parameters on the command line when you run the task For example if you want the task imheader to print header information on the file myfile hhh you can type st gt imhead myfile hhh IRAF does not require you to type the complete command name only enough of it to make it unique For example dir is sufficient for direc tory Escaping System Level Commands To run
138. agraphic data the presence of a bright source commonly induces the vertical streaks known as the Mr Staypuft effect see section 4 6 3 Because of the bright coronagraphic target it is not possible to fit simple medians to columns along the entire y axis length of the image in order to measure and subtract the Mr Staypuft streaks It may be possible to remove or at least reduce the streaks using a correction image derived from the bottom rows of the image only far from the coronagraphic target The first 19 rows are usually the only area of the image that is not intersected by the bright diagonal diffraction spike emanating from the hole You may use blkavg to average the first 19 rows and then blkrep to stretch this row average to form a 2 dimensional image to be subtracted from your data Care must be taken to ensure that bad pixels hot or cold pixels or grot do not bias the row average if necessary interpolate over bad pixels using fixpix NICMOS 5 40 Chapter 5 Data Analysis Figure 5 7 Coronagraphic image F110W filter Star centered in hole with image recalibrated left pedestal removed middle and with Mr Staypuft striping par tially corrected right Images are displayed with the same stretch recalibrated pedestal removed vertical bands removed In figure 5 7 above the correction for the Mr Staypuft bands is not perfect and shows the limitations of doing this The amplitude may modulate
139. ail help stsci edu Table of Contents Prelate ea pation da ns ix Introduction to Reducing HST Datta ccccceceetes ix Part I Introduction to Reducing HST Data Chapter 1 Getting HST Data 1 1 1 1 Archive Overvie W 0 ccccceseceteseeeseeeseeeeeeeeees 1 2 1 1 1 Archive REGIS ALON isiicccscicccss avivitieacnctectcecscavaeniees 1 3 1 1 2 Archive Documentation and Help eeeee 1 3 1 2 Getting Data with StarView 0 cece 1 4 1 2 1 Downloading and Setting Up StarView 1 4 1 2 2 Simple Use of StarView cc ssssssssseeeeeeeeeeeeees 1 4 1 2 3 Marking and Retrieving Data with StarView 1 9 1 2 4 Using StarView to Retrieve Calibration Files and Proposal Information cccceeeeeeeeeeeeeeees 1 9 1 2 5 Advanced Features of StarView eeee 1 10 1 2 6 StarView and the Visual Target Tunet 1 15 1 2 7 Quick Data Retrieval with StarView 008 1 15 1 3 Getting Data With the World Wide Web 1 16 1 4 Reading HST Data Tapes and Disks 1 17 iv HI Table of Contents Chapter 2 HST File Formate 2 1 2 1 Historical PerSpective cccceeeeeeteeteeeeeee 2 2 2 2 FS File FORMA a ee 2 3 2 2 1 Working with FITS Image Extensions 2 4 2 2 2 Working with FITS Table Extensions 00 2 9 2 3 GEIS File Formal see
140. ailable The second search and retrieval method is through the HST section of the MAST web site http archive stsci edu StarView is the more powerful of the two methods and in particular allows an examination of the calibration files applied to a given data file StarView also provides an interface to the Visual Target Tool VTT in the Astronomer s Proposal Tool APT suite of programs The VTT interface can display archive observations on a Digital Sky Survey DSS image alongside planned observations StarView is thus 1 1 1 1 1 2 Archive Overview HJ INTRO 1 3 recommended for observation planning duplication checking calibration file review investigation of On The Fly Reprocessing flags and proprietary status It is also recommended for those needing to retrieve large numbers of datasets and those needing to examine calibration files The MAST web site interface to the HDA has the same basic capabilities as StarView and may be preferable for those requiring simple retrievals of datasets Both StarView and the MAST web site allow simultaneous searches of the other MAST mission archives for all HDA searches They also offer simple preview of the capabilities of HST datasets when available as well as links to literature references citing a given dataset using the Astrophysics Data System ADS In later sections we discuss StarView and the MAST web site in more detail Archive Registration The simplest way to register and retrie
141. aken into account in the standard pipeline processing done for the HST Archive and the DARK reference files that have been available from STScI do not currently include temperature dependent shading Therefore if a particular observation was taken when the instrument was at a different temperature than that for which the standard DARK reference files were calibrated then residual errors in shading subtraction may result The effect is most noticeable for NICMOS Camera 2 because the amplitude of the shading is much larger for that camera Shading variations are much smaller and usually negligible for Cameras 1 and 3 The STScI NICMOS group has developed a fully temperature dependent model for shading in all three NICMOS cameras and has implemented a WWW based tool for generating temperature dependent dark reference frames see cures section 4 1 5 As of the time of this writing the STScI NICMOS group is also working to implement automatic temperature dependent dark correction in the calnica pipeline It is quite likely that this will be available by early 2002 and readers should check the STScI NICMOS WWW pages and NICMOS STANs for further updates Variable Quadrant Bias or Pedestal In addition to the net quadrant bias introduced at array reset there is some additional offset which is time variable and to some degree stochastic This variable quadrant bias has been described as the pedestal NICMOS 4 8 W Chapter 4 Anomalies and Err
142. al Tool APT package which has been created to aid astronomers in planning their HST observations during the Phase I and Phase II proposal stages see http apt stsci edu VTT is an image display tool which allows the user to display DSS images or local FITS images with proper World Coordinate System keywords in the headers It offers more features than JIPA which is the default StarView display tool However for a limited number of operating systems the VTT can be used with StarView VTT offers the particular advantage that it can overlay the instrument apertures of multiple observations on a single DSS image Clicking on these apertures will also highlight the associated datasets in StarView Currently to combine StarView and VTT requires downloading and installing APT from the above Web site APT is only available for those operating systems with the Java Virtual Machine 1 3 JVM 1 3 You can download the StarView VTT package with JVM 1 3 included a large download or if you already have JVM 1 3 installed you can get the smaller APT VTT package To make StarView use VTT you must change your Viewer options from JIPA to VTT Go to the Environment sub menu of Edit in StarView and change JIPA to VTT in the Viewers section If VTT is not listed here you should reinstall the two programs Following this change the Preview DSS and Overlay buttons of StarView should all bring up VTT Once VTT has been installed you can also bring up StarVi
143. al like effect The unpredictable nature of this variable quadrant bias means that it is not possible to remove it with standard reference frames In passing we note that it also considerably complicates the task of generating clean calibration reference files of any sort in the first place The user must attempt to determine the bias level from the data themselves and subtract it before flatfielding the data The difficulty then is determining the bias level independent of the sky source signal present in the data No one method has been developed which does this equally well for all types of NICMOS data The methods which have been tried depend on the nature of the target being observed e g sparse fields consisting mostly of blank sky NICMOS 4 10 Chapter 4 Anomalies and Error Sources 4 1 3 are treated differently from images containing large extended objects or crowded fields We discuss pedestal removal techniques in section 4 1 5 below Bias Jumps or Bands Occasionally spatial bias jumps sometimes called bands are seen in NICMOS images figure 4 4 These are apparently caused by a bias change when the amplifiers of one NICMOS camera are being used at the same time as another is reading out They are very commonly seen in the last readout of a MULTIACCUM sequence but may occasionally occur in intermediate readouts as well Figure 4 4 Bias jumps or bands in a NICMOS image Dark Reference Files Synthetic Dar
144. alibrated data files _cal fits the SAMP array contains the total number of valid samples used to compute the final science image pixel value obtained by combining the data from all the readouts and rejecting cosmic ray hits and saturated pixels In this case the sample array may have different values at different pixel locations less than or equal to the total number of samples in the MULTIACCUM sequence depending on how many valid samples there are at each location In the mosaic images _mos fits the data in the SAMP array indicate the number of samples that were used from overlapping images to compute the final science image pixel value Integration Time Image The TIME image is a floating point array containing the effective integration time associated with each corresponding science image pixel value These data are always computed in the ground calibration pipeline for recording in the raw data file For ACCUM and BRIGHTOBJ mode observations each pixel has the same time value For MULTIACCUM observations each pixel for a given readout has the same time value in the raw and intermediate data In these cases to save on data volume the image array is not cre ated and the value of the time is stored in the header keyword PIX VALUE in the TIME image extension see table 2 4 In MULTIACCUM calibrated data files _cal fits the TIME array contains the combined exposure time of all the readouts that were used to comp
145. alibration pipeline The task s internal algorithms operate on an unflatfielded image but a fully calibrated including flatfielding image may be used as input as the task will check the status of the flatfielding via the value of the FLATDONE keyword in the input image header and will temporarily remove and at the end of processing reapply the flatfield if necessary Note however that the FLATFILE used for the processing must be available locally in order to run pedsky Therefore if you wish to use this task on reduced data taken from the HST Archive be sure to retrieve the appropriate flatfield reference file as well Following the discussion in section 4 1 2 above let us say that a NICMOS image x y may be described as I x y S x y x O x y Bg where S x y is the incident astronomical flux sources plus sky background Q x y is the flatfield and B is the quadrant dependent bias offset The pedsky task works by minimizing the quantity 2ra 2 X Ey ly S x Qy By which is a measure of the total image variance as a function of the sky level S and four quadrant bias levels B Here we have made the simplifying assumption that the true incident flux S x y in a relatively blank field image can be approximated as a constant sky background S i e that there are no sources present In real data where there are real sources the quantity X includes a contribution due to the presence of actual objects in the image ab
146. alies and Error Sources Z Me data bias drifts and jumps and the net pedestal may still be present after standard processing Here we describe ways of handling each of these Residual Shading As described above the bias shading function is temperature dependent and may not be completely removed from data using the standard synthetic dark reference files This is particularly true for Camera 2 data where the shading amplitude is largest The STScI NICMOS group has now numerically modeled the temperature dependence of the shading and has made a temperature dependent dark generating tool available via the WWW This program that can generate synthetic darks for any NICMOS MULTIACCUM sequence and at any temperature within the NICMOS operating range When reprocessing NIC2 images the use of temperature dependent darks generated with the STScI WWW tool will often significantly improve the quality of the reduced data minimizing both shading residuals and pixel to pixel noise for non background limited data i e almost all NIC2 images taken through filters at wavelengths shorter than 1 8 microns You may extract the appropriate detector temperature information from the NDWTMP11 and NDWTMP13 key words in the _spt fits files Use NDWTMP11 for NICI or NIC2 and NDWTMP13 for NIC3 Variable Quadrant Bias or Pedestal Variable quadrant bias or pedestal is not removed by standard processing STScI has distributed several STSDAS tools
147. ality file pedigree values GROUND dd mm yyyy for reference files originated from Thermal Vacuum data INFLIGHT dd mm yyyy for reference files originated from on orbit calibration observations Detector read noise file pedigree values GROUND dd mm yyyy INFLIGHT dd mm yyyy Detector non linearity file pedigree values GROUND dd mm yyyy INFLIGHT dd mm yyyy Dark current file pedigree values GROUND dd mm yyyy INFLIGHT dd mm yyyy and MODEL dd mm yyyy for the synthetic darks see chapter 3 Flat field file pedigree values GROUND dd mm yyyy INFLIGHT dd mm yyyy Photometric calibration table pedigree values GROUND dd mm yyyy INFLIGHT dd mm yyyy Background model parameters table pedigree values GROUND dd mm yyyy INFLIGHT dd mm yyyy Calnica Calibration Switches allowed values PERFORM OMIT Correct wrapped pixel values MULTIACCUM zero read signal correction Subtract MULTIACCUM zero read Data quality initialization DQ array Calculate statistical errors ERR array Correct for detectors non linearities Dark correction Bars correction Flat field correction Convert to count rate Populate photometry keywords Identify cosmic ray hits update of DQ arrays in _ima fits output of calnica for MULTIACCUM Calculate background estimates Generate user warnings Calnica Calibration Indicators output from calnica values PERFORMED SKIPPED OMITTED BIASDONE ZSIGDONE ZOFFDONE MASKDONE NOISDONE NLINDONE DARKDONE BARSDON
148. and ACS imsets comprise three images SCI ERR DQ while NICMOS imsets comprise five SCI ERR DQ SAMP TIME All images belonging to the same imset share the same integer value of the EXTVER keyword given in the fourth column of a catfits listing Several STSDAS tasks can work with entire imsets see section 3 3 3 but most operate on individual images See the Data Structure chapters of STIS ACS and NICMOS Data Handbooks for more information on the contents of imsets INTRO 2 6 W Chapter 2 HST File Formats Table 2 1 NICMOS MULTIACCUM Listing from catfits tt gt catfits n3t50lc2r_ raw fits EXT FITSNAME n3t50lc2r raw IMAGE IMAGE IMAGE IMAGE 0 1 2 3 4 5 IMAGE 6 IMAGE 7 IMAGE 8 IMAGE 9 IMAGE 10 IMAGE FILENAME EXTVE DIMENS BITPI OBJECT n3t50lc2r_ raw fits 16 n3t501lc2r_ raw f SCI 1 256x256 16 n3t501c2r_raw f ERR 1 32 DQ 1 16 SAMP 1 16 TIME 1 32 SCI 2 256x256 16 ERR 2 32 DQ 2 16 SAMP 2 16 TIME 2 32 Accessing FITS Images After you have identified which FITS image extension you wish to process you can direct an IRAF STSDAS task to access that extension using the following syntax fitsfile fits extension number keyword options image section Note that all the bracketed information is optional However the only time it is valid to provide only a file name without further specification is when the file is a simple FITS file that contains a single image in the primary HDU Desig
149. apable of reading and writing files to and from remote systems on a network This feature is often used with tasks in the fitsio and convfile packages or with image display tasks The STSDAS Users Guide and the online help type help networking describe how to enable this feature To specify that you want to use the IRAF networking feature type the remote host name followed by an exclamation point followed by the file or device name For example ra mta Directory Navigation To navigate through directories you can use the following commands e path or pwd Lists the current working directory e cd directory Move to the named directory A 2 7 Troubleshooting There are a couple of easy things you can do to make sure that you don t have a simple memory or parameter conflict common causes of problems e Look at the parameter settings and make sure that you have specified reasonable values for every parameter Appendix A Getting IRAF and STSDAS W APP A 15 e When you run an IRAF task for the first time in a session IRAF stores the executable file in its process cache If IRAF appears not to be running your tasks properly you may need to use the flprcache command to clear the process cache To do this type lpr Some times you will need to execute this command twice in succession e Occasionally you may need to logout of the CL restart IRAF and try your command again If you still have a problem contact the STSc
150. are populated known as generic conversion 6 The raw data are calibrated using a standard set of NICMOS calibra tion programs calnica and calnicb The calibration software used by the pipeline step 6 above is exactly the same as that provided within STSDAS see section 3 2 The calibration files and tables used are taken from the Calibration Data Base System CDBS at STScI and are the most up to date versions available at the time the data are requested and processed by OTFR Sometimes however NICMOS Calibration Software W NICMOS 3 3 improved calibration reference files are created later and this is one reason why you may wish to reprocess your data see section 3 5 3 2 NICMOS Calibration Software 3 2 1 The Calibration Pipeline The science data that an observer receives are calibrated in the pipeline by at least one and possibly two STSDAS calibration routines calnica and calnicb The two routines perform different operations 1 calnica This routine removes the instrumental signature from the science data It is the first calibration step and is applied to all NIC MOS datasets individually Calnica operates on the raw science data files 2 calnicb This routine operates on associations it co adds datasets obtained from multiple iterations of the same exposure mosaics images obtained from dither patterns and background subtracts images obtained from chop patterns Calnicb is applied to the cali brated scienc
151. arly catastrophic consequences for coronagraphic data It is therefore important to use a flatfield where the hole is in a substantially different location e g a pre flight flat field from thermal vacuum testing or from early in SMOV when the hole location was very different or a flat where the hole has been patched The current generation of NIC2 flat field reference files available from the STScI calibration database have the hole patched This should be suitable for most purposes although the patches are not perfect and it is possible that small mismatches may still affect coronagraphic science Also the preflight flat fields were obtained at a different instrument temperature and because the flat field structure is known to vary with temperature the preflight flats will not provide a perfect match to on orbit data A future release of NIC2 flat fields should include better hole patches For reference table 5 8 lists the preflight Camera 2 flat fields Table 5 8 NICMOS Camera 2 preflight calibration flat field files filter flat field filter flat field F110W h1s1337cn F207M h1s1337mn F160W h1s1337dn F212N h1s1337nn F165M h1s1337en F215N h1s13370n F171M h1s1337fn F216N h1s1337pn F180M h1s1337gn F222M h1s1337qn F187N h1s1337hn F237M h1s1337rn F187W h1s1337in POLOL h1s13380n F190N h1s1337jn POL120L h1s1337sn F204M h1s1337kn POL240L h1s1337tn F205W h1s1337In Contemporary Hole Flats Calibration using contemporary fl
152. at fields would remove the very strong hole edge gradient resulting from calibration with a non contemporaneous hole image or with a patched flat The F160W filter acquisition lamp on off paired images obtained as part of the Mode 2 target acquisition process can be used to create a flat field reference file The hole position in these images is at the same location as the hole position in the associated coronagraphic observations Reference files created from these images would be Coronagraphic Reductions J NICMOS 5 37 appropriate for regions close to the coronagraphic hole The S N for these F160W filter reference files would be S N 100 Note the recommended standard calibration reference files have high Sel S N typically 1200 and should be used for regions far from the coronagraphic hole The Mode 2 acquisition F160W filter lamp and Z background images will usually contain an overexposed image of the target For completeness the following processing steps to create a contemporary flat field from the ACQ images are listed to assist the user ni gt ni gt gt gt gt hedit hedit hedit hedit hedit hedit calnica n4xj13jwq_rwb fits calnica n4xj13jwq_rwf fits n4xjl3jwq_rwb fits 0 flatcorr n4xjl13jwq_rwb fits 0 unitcorr n4xj13jwq_rwb fits 0 photcalc n4xjl3jwq_rwf fits 0 flatcorr n4xjl3jwq_rwf fits 0 unitcorr n4xjl3jwq_rwf fits 0 photcalc mssplit n4xj13jwq_clb fits mssplit n4xj
153. at longer wavelengths although this has not yet been empirically verified Aperture Correction It is often difficult to measure the total flux of a point source due to the extended wings of the PSF diffraction spikes and scattered light Such measurements are particularly difficult in crowded fields where the extended wings of sources can overlap with each other An accurate method of measuring the integrated flux in these situations could consist of several steps 1 Measure in the image the total counts within a small radius 2 Simulate the TinyTim PSF for the particular camera filter combina tion and position in the detector TinyTim allows the user to simulate PSFs with various focus settings and users concerned with small focus variations should be careful to set these parameters to the val ues appropriate for their observations This will have the largest effect for NIC3 data taken outside the refocus campaigns 3 Use the simulated PSF to measure the fraction of total flux within the photometry aperture To obtain the total flux of the source the countrate then only needs to be multiplied by the PHOTFNU or PHOTFLAM value and by the inverse of the measured fraction obtained in step three above Empirical PSFs could also be used for the above mentioned method There was no special Cycle 7 calibration program to obtain PSF measurements for all camera and filter combinations A significant amount of PSF data does exist in the a
154. ata Handbook is being written in late 2001 as we approach servicing mission 3b SM3b and the installation of the NICMOS Cooling System NCS Therefore the material presented in this volume are based on the experience gained in NICMOS during Cycles 7 and 7N before the cryogen was exhausted When NICMOS is revived with NCS undoubtedly there will be differences in its performance and characteristics At the very least it is expected to operate at a warmer temperature This will lead to differences in calibration in Cycle 11 and beyond as many of the instrument properties are temperature sensitive e g dark current bias behavior quantum efficiency and hence photometric calibration Moreover the NCS itself may introduce other changes in the way the NICMOS data are calibrated and analyzed depending on the temperature stability it achieves Another significant change from previous cycles is the difference in NICMOS commanding and operations which includes automatically obtaining dark frames after each HST passage through the South Atlantic Anomaly SAA While this handbook provides comprehensive information for treatment of the NICMOS data obtained during cycles 7 and 7N most of the material presented here are also applicable for observations in Cycle 11 and beyond Sometime after SMOV3b and once the in orbit performance of the NICMOS NCS is well understood we expect to provide a major update of this handbook 2 HE NICMOS Introduction
155. ata by the OPUS pipeline Note that trailer files are formatted with 132 columns Appendix B Associations IJ APP B 5 B 3 Associations The STIS and NICMOS calibration pipelines sometimes produce single calibrated images from associations of many exposures These associations allow HST pipeline processing to proceed further than it has in the past For example a NICMOS observer might specify a dithering pattern in a Phase II proposal NICMOS would then take several exposures at offset positions and the pipeline would combine them into a single mosaic In this case the original set of exposures constitutes the association and the mosaic is the association product Similarly a STIS observer might specify a CR SPLIT sequence in a Phase II proposal STIS would gather several exposures at the same pointing and the STIS pipeline would process this association of exposures into single image free of cosmic rays that would be the association product When you search the Archive with StarView for observations involving associations of exposures your search will identify the final association product The rootnames of association products always end in zero see figure B 1 above If you request both Calibrated and Uncalibrated data from the Archive you will receive both the association product and the exposures that went into making it The corresponding association table located in the file with suffix asn and the same rootname as the associat
156. ata flag NOT on throughout observation Pipeline Processing Summary any problems encountered in the routine pipeline processing of the data are listed Calibration Data Quality Summary possible problems with the cal ibration reference files is summarized for example any dummy ref erence files used in the calibration would be identified Thumbnail plots the individual exposures for dithered chopped and NUMITER gt 1 observations are given Observing Pattern a schematic cartoon of the observing pattern is shown Dither Chop Mosaics plots of the mosaiced calibrated image on target and average mosaiced background image off target are included Data Quality Summary a summary of the spacecraft performance pipeline processing status and calibration data quality for each expo sure Calibration Reference File Summary a summary of the calibration processing switches and reference files used to process each expo sure NICMOS 2 24 Chapter 2 Data Structures CHAPTER 3 Calibration In this chapter 3 1 Pipeline Processing OTFR and the HST Archive 3 1 3 2 NICMOS Calibration Software 3 3 3 3 Basic Data Reduction calnica 3 5 3 4 Mosaicing calnicb 3 16 3 5 Recalibration 3 23 This chapter is designed to help you understand the steps that are performed on your data in the routine pipeline process and to help you decide whether you should recalibrate your data In this chapter we e prov
157. ata quality DQ array for each imset where the bars occur e g by setting the DQ values to the bad data flag value 256 Subsequently when calnica carries out the CRIDCALLC step fitting the counts versus time to determine the count rates it will ignore flagged pixels in a given imset and the bars will therefore not perturb the fits A memo describing this procedure is available as a link from the STScI NICMOS Data Anomalies WWW page lv_ A new pipeline processing step BARSCORR is implemented in calnica version 3 3 and higher see section 3 3 Reprocessing images z using this step may eliminate many problems with bars Detector Nonlinearity Issues J NICMOS 4 21 If a bar appears in the zeroth readout it will be subtracted from all the other readouts as part of the normal calibration process ZOFFCORR and appear as a negative bar pattern in all readouts of the processed x ima fits file This should have no significant effect on the calibrated final image _cal fits however since the bar just acts as an intercept offset to fit of counts vs time which is irrelevant to CRIDCALC which only computes the slope i e the count rate Figure 4 5 Bars in a NICMOS camera 1 image 4 3 Detector Nonlinearity Issues 4 3 1 New Nonlinearity Calibrations The response of the NICMOS detectors is inherently nonlinear As was described in section 3 3 the calnica pipeline applies a nonlinearity correction with the step NLINCORR Ear
158. atasets in an Association Keyword Purpose a G INSTRUME Check whether they are NICMOS data CAMERA Camera number FILTER Filter name if set to BLANK the association is made of darks IMAGETYP Type of image EXT external DARK dark frames FLAT flat field images NUMITER Number of iterations for each exposure PATTERN Pattern used NUMPOS Number of independent positions in the pattern A second set of header keywords table 3 4 are specific to each member of the association and must be read from each input image NICMOS 3 20 Chapter 3 Calibration Table 3 4 Dataset specific Keywords Keyword Purpose PATT_POS Position of the image in the pattern BACKESTn Background estimates from calnica CRPIXn World Coordinate System WCS information see table 2 3 CRVALn CDn_n CTYPEn Based on this information an inventory is taken of which input images exist where they belong in the pattern how many images there are at each pattern position which images belong to the target field which ones are from background fields and to which output mosaic image each input image will contribute As part of the input process the appropriate ILLMFILE reference file is loaded Note however as is discussed below under Background Estimation and Removal the ILLMFILEs used in this step are dummies and have no effect on the data In fact the ILLMFILEs provided by STScI have their PEDIGREE set to DUMMY thus fo
159. ate and NREAD The data quality flags set in the DQ image of the NOISFILE are propagated into the DQ images of all image sets imsets being processed Because the noise calculation is performed before dark subtraction has taken place the noiseless electronic signal component known as shading see DARKCORR below is still present in the data In calnica versions 3 3 and later the NOISCALC step estimates the level of the shading signal in the data by computing column or row statistics in the DARKFILE Basic Data Reduction calnica IJ NICMOS 3 11 reference file The computed shading estimate is subtracted from the signal in the science image when computing Poisson noise on the detected counts This yields a more accurate noise estimate than what was produced in earlier versions of the pipeline Throughout the remaining steps in calnica the error image is processed in lock step with the science image getting updated as appropriate Errors are mostly propagated through combination in quadrature For MULTIACCUM data sets the ERR array for the final calibrated image _cal fits is populated by the CRIDCALC step of calnica based on the calculated uncertainty of the count rate fit to the MULTIACCUM samples In general the values in the error images should only be regarded as an estimate of the data uncertainties The precise pixel noise values in NICMOS images are difficult to compute a priori because many fac tors may contribute sometimes
160. ate passband shapes for any combination of these elements It can also generate synthetic spectra of many different types including stellar blackbody power law and H II region spectra and can convolve these spectra with the throughputs of HST s instruments You can therefore use it to compare results in many different bands to cross calibrate one instrument with another or to relate your observations to theoretical models One useful application of synphot is to recalculate the value of PHOTFLAM for a given observation using the latest calibration files For example to recalculate PHOTFLAM for an FOC observation you could use the calcphot task in synphot as follows sy gt calcphot foc f 96 x96zlrg f501n unit 1 flam counts The first argument to calcphot gives the instrument and its configuration in this case the FOC f 96 camera in full zoomed format with the F501 filter See the obsmode task in synphot and the Synphot User s Guide for help with these observation mode keywords The second tells the task to model a flat F spectrum having unit flux and the third tells the task to produce output in units of counts per second After you run calcphot its result parameter will contain the count rate expected from the FOC given this configuration and spectrum The PHOTFLAM INTRO 3 20 Chapter 3 STSDAS Basics keyword defined to be the flux required to produce one count per second simply equals the reciprocal of this valu
161. ation log files share the same rootname as the observation they are associated with except for the final character which for observation log files is always a j see appendix B for more on the names of HST data files When OMS was installed in October 1994 it initially generated files with the suffixes cmh cmj cmi which contained header information high time resolution pointing data and three second average pointing data respectively see table C 1 OMS observation logs changed to the jih jid jif image format after August 1995 at which time the cmi table was renamed jit to keep the naming convention consistent In the OMS version of August 1995 cmj tables were replaced with a jitter image which is a two dimensional histogram of jitter excursions during the observation The suffixes of the GEIS jitter image are jih for the header and jid for the image data The jit table accompanies the jitter image The header file of the image replaces the cmh file but includes the same information with the addition of some image related keywords A detailed description of the observation log files can be found on line http www stsci edu instruments observatory obslog OL_1 html Table C 1 OMS Observation Log Files Suffix Contents October 1994 to August 1995 cmh OMS header cmj High time resolution IRAF table cmi Three second averages IRAF table _cmh fits Archived FITS file of cmh _cmj fits Archived FITS file
162. ations 1 Time Per Exposure DEF Special Requirements POS TARG 0 5 0 5 The science data file in the dataset will contain 13 imsets corresponding to the MULTIACCUM NSAMP 12 parameter plus the 0 th read and some of the header keywords will be filled with the relevant information from the target and exposure logsheets of the Phase II e g the keywords TARGNAME RA_TARG DEC_TARG From the Phase II Proposal to Your Data IJ NICMOS 2 21 The next example shows an exposure logsheet entry that will generate both multiple datasets and an association Exposure Number 1 Target _Name HDF Config NIC2 Opmode MULTIACCUM Aperture NIC2 Sp_Element F160W Optional Parameters PATTERN SPIRAL DITH CHOP NUM POS 8 DITH SIZE 1 5 CHOP SIZE 25 0 SAMP SEO STEP256 NSAMP 12 Number of Iterations 1 Time Per Exposure DEF Special Requirements In this observation eight datasets one for each position of the pattern and one association will be created The pipeline products will include the eight reduced datasets one mosaic of the background subtracted target and one mosaic of the background An association will be generated also in the case below Exposure Number 1 Target _Name HDF Config NIC2 Opmode MULTIACCUM Aperture NIC2 Sp Element F160W Optional Parameters SAMP SEQ STEP256 NSAMP 12 NUMBER_of Iterations 3 Time Per Exposure DEF Special Requirements The number of iter
163. ations is 3 implying that three datasets will be generated from this exposure logsheet plus an association table containing the three datasets The collection of multiple iterations into an association is a new feature introduced by the NICMOS and STIS pipelines In our specific example the co added image from the three iterations will be one of the products of the pipeline NICMOS 2 22 Chapter 2 Data Structures 2 5 Paper Products After the data from an observation have been received and processed through the STScI pipeline PDF files paper products are automatically generated which summarize the data obtained The paper products may also be generated by the observer using the stsdas hst_calib paperprod task pp_dads to provide a first look at the observations and their quality Here we briefly describe the NICMOS paper products As of 1 August 1999 the Archive is no longer printing paper copies of the paper products for new observations The PDF files must now be retrieved via the WWW from http archive stsci edu hst pdf_search html Paper products typically summarize the set of exposures that constitute a visit in the Phase II proposal The set of exposures can be either individual datasets or associations Paper products are produced by accessing the appropriate keywords in the dataset headers or in the association tables A given page of the NICMOS paper products falls into one of two categories visit level page o
164. ay not match the QE response pattern measured in the flatfield In cases like these you may want to provide your own sky images for use by pedsky rather than rely on the flatfield reference files to represent the shape of the sky One possibility would be to use sky frames constructed from the median of many dithered science or background exposures This can sometimes improve the quality of the sky pedestal fitting even for data taken at shorter wavelengths This was the approach taken for STScI reductions of the HDF South NICMOS data for example Another possibility especially for long wavelength data might be to use a specially constructed color dependent flat field see section 4 4 2 The pedsky help pages give further information about this task and its parameters including guidance for how to use images other than the flatfield as the sky model pedsub As described above the pedsky task requires lots of blank sky to be effective and will only work on relatively sparse NICMOS images The pedsub task provides an alternative method for images which contain larger objects that fill the field of view The basic methodology for pedsub NICMOS 4 18 J Chapter 4 Anomalies and Error Sources is essentially the same as that of pedsky modeling the image as the sum of a constant per quadrant pedestal offset plus an astronomical signal sky objects that is modulated by the flatfield and then loops over a range of trial values for the
165. ble Tabulated STIS spectra are stored as data arrays within individual cells of FITS binary tables see section 2 2 2 These tables are effectively three dimensional with each column holding a particular type of quantity e g wavelengths fluxes each row holding a different spectral order and each cell holding a one dimensional array of values spanning the wavelength space of the order The txtable in the tables ttools package extracts these data arrays from the cells specified with the selectors syntax and stores them in the columns of conventional two dimensional binary tables For example suppose the first extension of the FITS file data fits contains a STIS echelle spectrum and you want to extract only the wavelength and flux arrays corresponding to spectral order 68 You could then type tt gt txtable data fits 1 c WAVELENGTH FLUX r sporder 68 gt gt gt out_table INTRO 3 30 Chapter 3 STSDAS Basics This command would write the wavelength and flux arrays to the columns of the output table out_table To specify multiple rows in a tabulated echelle spectrum you would type tt gt txtable data fits 1 c WAVELENGTH FLUX r row 10 12 gt gt gt echl 3 5 3 This command would generate three separate output files named echl_ r0010 tab echl_ r0011 tab andechl_ r0012 tab See the online help for more details on txtable and the selectors syntax and remember to include the double quotation mark
166. ble or the calibration software has changed significantly you may choose to recalibrate your data using the new files or software Finding that a calibration reference file has changed since your data were calibrated doesn t always mean that you have to recalibrate The decision depends very much on which calibration image or table has changed and whether that kind of change to your data is likely to affect your analysis in a significant way Before deciding to recalibrate you might want to retrieve the new recommended reference file or table and compare it to the one used to calibrate your data at STScI in order to determine if the differences are important You can use the table tools in the IRAF ttools package to manipulate and examine calibration tables Reference files can be manipulated in the same way as your science data Finally the observations may have been made in a non standard way Some of the input files e g _asn fits may require manual editing before recalibration Recalibrating the Data This section describes the mechanics involved in actually recalibrating a dataset As noted above the simplest way to recalibrate your data is to retrieve it again from the HST Archive using OTFR However it is sometimes more convenient to simply reprocess your raw data locally using the latest pipeline software or reference files In some cases when you may wish to use special customized reference files or processing software local
167. bout the files Docu mentation is available via the WWW at http www stsci edu instru ments observatory obslog OL_1 html APP C 16 jf Appendix C Using Observation Logs A absolute photometry NICMOS NICMOS 5 17 absolute spectrophotometry NICMOS grism NICMOS 5 18 ACCUM mode NICMOS NICMOS 1 5 accuracy astrometric improving INTRO 3 11 acquisition failure guide stars APP C 11 algorithm calnica NICMOS 3 5 calnicb NICMOS 3 19 analog to digital conversion NICMOS NICMOS 3 9 analysis images general in STSDAS INTRO 3 9 spectra general in STSDAS INTRO 3 24 spectra general tasks in IRAF INTRO 3 30 spectra STIS INTRO 3 27 analysis package image analysis INTRO 3 4 aperture NICMOS correction NICMOS 5 15 apphot package aperture photometry INTRO 3 17 archive file names INTRO 2 1 arithmetic imset msarith task INTRO 3 15 spectra splot task INTRO 3 31 Index array FITS table INTRO 2 11 NICMOS readout NICMOS 1 4 association table NICMOS NICMOS 2 9 association table NICMOS NICMOS 2 2 NICMOS 2 9 astrometry basic in STSDAS INTRO 3 10 improving accuracy INTRO 3 11 tasks in STSDAS INTRO 3 11 B background NICMOS NICMOS 3 15 NICMOS 3 21 running tasks in APP A 7 bias correction NICMOS NICMOS 3 9 BRIGHTOBJ mode NICMOS NICMOS 1 6 C calibrated science file NICMOS NICMOS 2 2 calibration NICMOS grism spectroscopy NICMOS 3 4 re calibrat
168. box bj y bz9x baj xy b22 y where the origin of the x y coordinate system is chosen to be coincident with that of x y i e pixel 128 128 of the array As defined by Cox et al the distortion corrections explicitly do not account for the X and Y scale difference described above and therefore aj and b are fixed at 1 Also a7 the linear dependence of x on y is held at 0 although bzo is derived in the fit This fixes the y axis orientation but allows for departures from orthogonality The fitted coefficients for the three cameras are given in table 5 5 Table 5 5 NICMOS Geometric Distortion Coefficients NIC 1 NIC 2 NIC3 Coefficient value value value ajo 1 0 0 0 1 0 0 0 1 0 0 0 a20 10 9e 6 1 4e 6 9 98e 6 0 85e 6 2 78 e 6 2 59e 6 a1 10 6e 6 5 9e 6 1 17e 6 0 26e 6 17 3e 6 6 02e 6 a7 7 Ae 6 2 6e 6 4 45e 6 0 71e 6 6 02e 6 2 05e 6 bio 48 5e 4 1 7e 4 2 97e 4 0 53e 4 16 3e 4 0 12e 4 by 1 0 0 0 1 0 0 0 1 0 0 0 bao 5 0e 6 1 4e 6 1 02e 6 0 82e 6 15 44e 6 1 75e 6 bo 10 7e 6 4 5e 6 2 57e 6 0 73e 6 3 34e 6 3 84e 6 boo 14 4e 6 2 1e 6 0 15 6 1 27e 6 4 26e 6 2 13e 6 NICMOS 5 22 Chapter 5 Data Analysis 5 4 4 5 4 5 After applying this distortion correction remember to add 128 to each of the x and y values to transform the origin back to pixel position 128 128 Also remember that the above solution does not correct the X Y scale differences described above The p
169. brate data using the same software as the routine calibration pipeline at STScI NICMOS 3 4 Chapter 3 Calibration 3 2 2 Software for Grism Data Reduction Vv A unique capability of NICMOS is the grism mode which permits multi object slitless spectroscopy at low resolution Grism data are processed with separate calibration software calnicc which performs a series of steps that identify and extract spectra from the images The inputs to calnicc are the calibrated images _cal fits produced by calnica Calnicc was developed using the Interactive Data Language IDL software at the Space Telescope European Coordinating Facility ST ECF The manual written by W Freudling and R Thomas describing the software its installation and use can be found at the ST ECF calnicc web site Currently calnicc is not part of the automatic pipeline processing and users must apply the calibration software to their grism images Many users may want to start the spectrum extraction processing using NICMOSlook the interactive counterpart to calnicc NICMOSlook is written in IDL and is a quick look spectrum extraction tool for grism spectra Unlike calnicc NICMOSlook requires users to specify parameters interactively e g the best way to find an object the weights to be given in the spectral extraction This tool is recommended for first time users or users with a small number of grism data Once you are familiar with the extraction proce
170. c hole is visible in the NIC2 image NIC1 NIC2 NIC3 4 4 2 Temperature dependent Flatfields As with the dark current and bias the quantum efficiency of NICMOS detectors is a function of the detector temperature Because the instrument temperature varied somewhat throughout Cycle 7 the flat field structure also varied slightly due to this effect For the temperature range experienced during Cycle 7 this was a relatively small effect a few percent but careful users may wish to recalibrate their data using flat fields customized for the operating temperature of the instrument at the time of their observations The process here is essentially identical to that described in section 4 1 5 for temperature dependent dark correction The STScI NICMOS group has created a WWW based tool that will generate temperature specific flat fields appropriate for any NICMOS camera and filter over a range of detector temperatures This capability may become particularly important in Cycle 11 and afterward when the NICMOS Cooling System NCS is expected to result in instrument operations at a substantially higher temperature than was used in Cycle 7 ar Detector temperatures are stored in the NDWTMPI11 and NDWTMP13 keywords in the _sptfits files For Cameras 1 and 2 use NDWTMP11 for Camera 3 use NDWTMP13 N 4 4 3 Color Dependence of Flatfields The strong wavelength dependence of the NICMOS response may affect the quality of flatfielding
171. calnica see chapter 3 The input to calnica are the raw images For a MULTIACCUM exposure this file contains a single science image formed by combining the data from all samples Intermediate Multiaccum Science File _ima This FITS file is also produced by the pipeline task calnica and contains the calibrated science data for all samples of a MULTI ACCUM dataset before the process of combining the individual readouts into a single image has occurred This file is only pro duced for MULTIACCUM observations NICMOS Data Files I NICMOS 2 3 Mosaic Files _mos These FITS files contain the composite target and for chopped pattern sequences background region images constructed by the pipeline task calnicb for an associated set of observations see chapter 3 The input to calnicb are the calibrated cal images from calnica and the _asn association table Target images are co added and background subtracted The value of the last charac ter of the rootname is 0 for targets and 1 to 8 for background images These files are only produced for an associated set of observations Post calibration Association Table _asc This table is produced by the pipeline calibration task calnicb and is the same as the association table _asn with the addition of new columns which report the offsets between different images of the mosaic or chop pattern as calculated by calnicb and the back ground levels computed for each image This file is only p
172. ch extension can contain one of several different data types including images INTRO 2 4 W Chapter 2 HST File Formats binary tables and ASCII text tables The value of the XTENSION keyword in the extension s header identifies the type of data the extension contains Figure 2 1 schematically illustrates the structure of a FITS file and its extensions Figure 2 1 FITS File Structure PRIMARY HEADER DATA EXTENSION HEADER Extension 1 DATA EXTENSION HEADER Extension 2 EXTENSION Extension 3 HEADER The three letter identifier e g dOh that follows the rootname of an HST data file see appendix B for more on HST file names has often T been called an extension in the past However because of the poten tial for confusion with FITS extensions this handbook will refer to these three letter identifiers as suffixes 2 2 1 Working with FITS Image Extensions The FITS image kernel included in IRAF version 2 11 is designed to read and write the images in FITS extensions and their associated headers Once IRAF has ingested a FITS image and its header it treats the header data pair like any other IRAF image The following discussion describes how to specify the image extensions in FITS files that you would like to process with IRAF STSDAS tasks and presumes that you are using IRAF 2 11 or higher It covers how to e Lista FITS file s extensions e Access data in particular FITS ext
173. column Quit implot Move down Move up FEU GIEe Space Display coordinates and pixel values Analyzing HST Images W INTRO 3 13 Figure 3 4 Plotting Image Data with implot STSDAS calcomp gkidir imdkern phistogram sgidecode surface contour gkiextract implot pradprof sgikern velvect ertpict gkimosaic nsppkern prow showcap gdevices graph pcol prows stdgraph gkidecode hafton pcols pvector stdplot pl gt dir wk wOmwO502t cOd wOmwO502t cOh wOmwO502t d0h Pl gt implot wOmw0502t cOh 200 tektronix Tek NOAO IRAF V2 10EXPORT stevens lager stsci edu Fri 16 07 15 20 Aug 93 e 200 of wOmw0502t coh WOMWOSO2TL1 4I T T T Plot line 200 of a WF PC 1 image To Print This Plot Press Type gflush to flush the buffer imexamine The IRAF imexamine task in the images tv package is a powerful task that integrates image display with various types of plotting capabilities Commands can be passed to the task using the image display cursor and the graphics cursor A complete description of the task and its usage are provided in the online help available from within the IRAF environment by typing help imexamine INTRO 3 14 Chapter 3 STSDAS Basics Table 3 3 Image Manipulation Tasks Task Package Purpose boxcar gcombine gcopy geomap geotran grlist gstatistics imcalc imedit imexamine
174. commonly available on most Unix systems but are not standard in the VMS environment The examples shown below reflect Unix usage If you are on a VMS system you should consult with your systems support staff regarding the availability and usage of these commands To process the files on a Unix system 1 Get the compressed tar file that you want as described in previous sections 2 Make an appropriate subdirectory using the mkdir command 3 Pipe the compressed tar file through the uncompress and tar files to expand and unpack the file APP A 18 Appendix A Getting IRAF and STSDAS The following example shows how to do this The example assumes that you are putting the files in a subdirectory under usr iraf stdata note that the name of your file here is assumed to be XXX tar Z pwd usr iraf stdata mkdir XXX mv XXX tar Z XXX cd XXX cat XXX tar Z uncompress tar xf APPENDIX B HST File Names In this appendix B 1 Rootnames B 2 B 2 Suffixes of Files Common to all Instruments B 3 B 3 Associations B 5 This appendix describes the syntax of HST data file names which encode a large amount of information about the files themselves Datasets retrieved from the Archive as described in consist of multiple files in FITS format each with a name that looks like this ipppssoot_sfx fits Rootname if ae Format Data Type FITS e Rootname The first part of the file na
175. cribed in the instrument sections of this handbook and stores both calibrated and uncalibrated datasets in the Archive Pipelines of older instruments FOC FOS FGS GHRS HSP WF PC 1 and WFPC2 generate files in the so called GEIS stands for Generic Edited Information Set format Since GEIS is a machine dependent format these files are converted to a specific kind of FITS file format sometimes referred as waiver FITS before being archived We ll explain the structure of this waiver FITS format later in this chapter Since the waiver FITS format is only designed for archival purpose it is necessary to convert it back to the GEIS format before further data processing and analysis using IRAF STSDAS tasks Instruments installed after the 1997 servicing mission STIS NICMOS ACS and most likely all future instruments have pipelines which generate FITS files directly They are ready to be used by relevant IRAF STSDAS tasks and unlike the waiver FITS files do NOT need to and indeed should not be converted to GEIS format Sometimes FITS files for the newer instruments are referred to as FITS with extension or extended INTRO 2 1 INTRO 2 2 9 Chapter 2 HST File Formats FITS files But this can be misleading since a waiver FITS file also has one ASCII table extension Much confusion has occurred about the two kinds of FITS files been archived at STScI So we like to repeat one more time
176. csec PAM Y tilt position arcsec PAM focus position mm Timing pattern identifier for readout Detector array readout rate FAST SLOW Sample time of MULTIACCUM zeroth read sec Horizontal clock rate microseconds Readout video bandwidth kHz Analog digital coversion zero level DN usually some large negative number Analog digital conversion gain electrons DN Photometry Keywords Combination of lt INSTRUMENT gt lt CAMERA gt lt FILTER gt Inverse sensitivity erg em angstrom DN Inverse sensitivity Jy sec DN ST magnitude system zero point Pivot wavelength of the photmode Angstrom Root Mean Square bandwidth of the photmode Angstrom SAA keywords for use with post SAA darks in Cycle 11 Time of last exit from SAA contour level 23 Seconds since last exit from SAA contour 23 Association name for post SAA dark exposures SAA cosmic ray map file Calnica Calibration Reference Files inputs to calnica Static data quality file Detector read noise file Detector non linearity file Dark current file Flat field file Photometric calibration table Background model parameters table Calnica Calibration Reference File Pedigree outputs from calnica Keyword Name MASKPDGR NOISPDGR NLINPDGR DARKPDGR FLATPDGR PHOTPDGR BACKPDGR BIASCORR ZSIGCORR ZOFFCORR MASKCORR NOISCALC NLINCORR DARKCORR BARSCORR FLATCORR UNITCORR PHOTCALC CRIDCALC BACKCALC WARNCALC Header Keywords J NICMOS 2 13 Meaning Static data qu
177. ction process 2 Postscript files of the extracted spectra image_n ps This file contains graphical representations of the extracted spectra One post script file for each spectrum is generated where n is a sequential number starting with 0 In addition a number of miscellaneous output files can be created by the software which include background image finding charts catalog files and object lists In NICMOSlook these files have to be explicitly requested while in calnicc files are created depending on the configuration of the program Processing Object Detection and Classification Objects on the direct images may be found by interactively using the cursor Automatic programs to find objects are also available NICMOSlook uses DAOFIND for that purpose while calnice uses Sextractor to find and classify objects It may sometimes be useful to use the grism images to search for particular types of spectra by eye In this case the spectral images can be NICMOS 5 50 Chapter 5 Data Analysis flatfielded using ordinary on orbit grism flatfields displayed and examined visually for e g emission line objects or very red spectra Ordinarily these on orbit flatfields are not used as part of NICMOS grism data processing instead the flatfielding is done on the extracted spectra as is described below Once the interesting objects have been identified their spectra should be extracted from non flatfielded grism images Loca
178. d mask offset thin lines The thick line is the difference between the two Right panels absolute value of counts difference as a percent of the counts for the PSF at the nominal cold mask offset ac i ne OE F160W 40 4 SOF J 205 q log normalized_counts counts difference 1 cal fae BE SY ee as 3 Fa an a OT a O T A a Se E 1 en Y fan PALA O 20 40 60 80 100120 O 20 40 60 80 100120 pixel pixel 1 1 T J O T 7 fe PLAN F187 40 SOF 20 log normalized_counts NS counts difference A ASP YNA meet rer wer pit Hii ss Lath O PER ENEA E eer vam ae Peer Jato 1 reer O 20 40 60 80 100120 O 20 40 60 80 100120 pixel pixel Counts Arbitrary PSF Subtraction W NICMOS 5 27 Figure 5 5 Illustration of PSF color dependence in different filters In F110W the 8000 K blackbody spectrum has a very different slope from that of the 3000 K blackbody Therefore the PSF resulting from images of point sources with these temperatures will be very different from one another The F187W filter however samples the Rayleigh Jeans regime for both temperatures resulting in spectra with about the same slope so the difference between the 8000 K PSF and 3000 K PSF will be very small 1200 800 600 400 200 Microns NICMOS 5 28 Chapter 5 Data Analysis Figure 5 6 Effect of
179. d out in each quadrant Since the shading function is very steep and highly nonlinear during this part of the readout it is the part of the array most sensitive to changes in the detector environment Thus it is thought that the pixels in these rows or columns are not any less sensitive but that they have just had an incorrect bias subtracted from them The result is a row or column of pixels that is either under or over corrected for the shading by the dark reference file Cures For some data it is possible to fit a function to the affected column and add it back in as a delta bias but the data in the affected pixels tends to be rather noisy as well Given dithered data you may be better off just treating the affected pixels as bad and using spatial dithers to recover that information just as you would do for other bad pixels As with grot section 4 5 1 adding the middle column row to the DQ array flags of the calibrated image _cal fits or to the MASKFILE before calnica processing will mark them for exclusion when dithered images are subsequently combined by calnicb Coronagraphic Hole NICMOS camera 2 includes a coronagraphic hole which can be used to partially obscure bright sources In non coronagraphic observations however the hole is still present and will partially or completely blank out any objects which fall near it For thermal IR images the hole can appear as a positive bump due to excess background emission shin
180. destructive The beginning of an integration is marked by the zeroth read which is always preceded by a reset Since all readouts are non destructive i e do not change the value of the charge accumulated on the pixel the last two steps of the sequence above can be repeated multiple times and the last read of the sequence will be called the final read The total integration time of an exposure is defined as the time between the final and the zeroth read of the first pixel in the array The scientific image is given by the difference between the final and the zeroth readouts Four readout modes have been defined for NICMOS exploiting the flexibility allowed by the non destructive reads e MULTIACCUM e ACCUM e BRIGHTOBJ e RAMP not available in Cycle 11 and beyond Each mode is described in the following sections with larger emphasis on MULTIACCUM which is by far the most used and best calibrated mode RAMP mode was never used for on orbit science observations during Cycle 7 and will no longer be implemented for use in Cycle 11 and beyond 1 2 1 1 2 2 Detector Readout Modes IJ NICMOS 1 5 MULTIACCUM In a MULTIACCUM MULTIple ACCUMulate exposure the zeroth read is followed by several other non destructive readouts during the course of a single integration All of the readouts are stored in the on board computer s memory and sent to the ground Because the readouts are non destructive accumulated counts are built up f
181. dial Profile Countrate 100 F 50 F lt P T g Eai a EG a S g 0 2 4 6 8 Radius pixels Figure 5 3 NIC2 Image with Radial Profile Image of Star Taken with NIC2 F237M PSF Radial Profile 200 150 8 100 50 J o E pen Pas mmh il 0 2 4 6 8 Radius pixels PSF Subtraction W NICMOS 5 25 5 5 1 Impact of Instrumental Effects on PSF Subtraction There are a number of factors which affect the NICMOS PSF and thus can impact the results of image analysis relying on PSF subtraction The factors are focus variations due to OTA breathing cold mask irregular motion wiggling on an orbital time scale PSF color dependence The limits to the accuracy of PSF subtraction imposed by these factors have been assessed using model PSFs generated by TinyTim software and synphot generated blackbody spectra The results for Camera 2 are given in table 5 6 below The mean and standard deviation of the PSF subtraction residuals are given a percentage of the nominal PSF pixel values The standard deviation can be interpreted as the average relative spatial noise expressed as a percent of the PSF pixel value at any given distance from the PSF center The mean represents a systemic component in the PSF residuals Table 5 6 Effect of focus variation cold mask wiggling and PSF color dependence on PSF subtraction mean mean mean mean mean mean effect of sigma sigma sigm
182. duced in an ACQ data set is presented in table 5 7 Table 5 7 NICMOS ACQ data image extensions Extension Image Contents ipppssoot_raw Raw target data ipppssoot_rwb Raw background data ipppssoot_rwf Raw flat field data ipppssoot_spt Target SHP and UDL information ipppssoot_spb Background SHP and UDL information ipppssoot_spf Flat field SHP and UDL information ipppssoot_cal Calibrated target data ipppssoot_clb Calibrated background data ipppssoot_clf Calibrated flat field data ipppssoot_trl OPUS processing trailer file ipppssoot_pdq OPUS Processing Data Quality file During Cycle 7 and 7 5 the exptime keyword for NICMOS ACQs was incorrectly populated A correction was installed in OPUS 9 4 on October 19 1998 Reuse Target Offset RTO and Interactive Acquisitions A variation of the Reuse Target Offset RTO capability was sometimes used to acquire and position bright targets into the coronagraphic hole This is known as Mode 1 acquisition see Schultz et al NICMOS ISR 98 019 Any target that would saturate the detector in the shortest possible Mode 2 ACQ ACCUM exposure time 0 228 seconds was considered to be a bright target The following discussion describes the necessary steps for a Mode 1 Reuse Target Offset RTO acquisition The RTO acquisitions were performed during the first visit and the science observations were obtained in a following second visit NICMOS 5 32 Jf Chapter 5 Data Analysis 5 6 3
183. duced sensitivity most likely due to flecks of anti reflective paint which were scraped off the optical baffles between the dewars as they were forced against each other by the solid nitrogen cryogen expansion The largest example known as the battleship is found in camera 1 and affects approximately 35 pixels However most grot seems to affect single pixels Scrape tests conducted at Ball Aerospace shortly after NICMOS was launched reveal that the paint flecks can range in size from 25um to greater than 100um Since NICMOS pixels are 40um on a side this means there is potential for grot smaller than 1 pixel Table 4 1 NICMOS Cosmetics Type NIC 1 NIC 2 NIC 3 Hot Pixels 68 94 17 Cold Pixels 10 11 3 Grot 284 227 288 Cures Dithering is the best way to guard against the effects of bad pixels and grot If you have multiple dither positions you can use the static masks and the grot masks to exclude bad pixels when combining the images e g with calnicb or with IRAF imcombine or with the STSDAS dither drizzle routines Or you may interpolate over masked pixels using e g IRAF fixpix Grot masks are available on the NICMOS instrument website and should be used to correct data taken between June 1997 and November 1998 For further description of these files see Sosey amp Bergeron 1999 ISR NICMOS 99 008 The grot masks are not presently used as part of the default calibration procedure and are only presented to warn users abo
184. dy exists and you want to append a new extension to it you need to include the APPEND option in the output file specification The following command appends extension sci 2 of fitsfile fits onto the existing file outfile fits while retaining the original EXTNAME and EXTVER of the extension the noinherit specification inhibits the copying of the primary header keywords from the input file into the output extension header cl gt imcopy fitsfile fits sci 2 noinherit gt gt gt outfile fits append 2 2 2 FITS File Format Hi INTRO 2 9 If you want to change the EXTNAME or EXTVER of the appended extension you can specify the new values of these keywords in the output extension like this cl gt imcopy fitsfile fits sci 2 noinherit gt gt gt outfile fits sci 3 append For obvious reasons it is not generally advisable for two file extensions in the same FITS file to share the same EXTNAME and EXTVER values However if you must append an extension to an output file already containing an extension with the same EXTNAME EXTVER pair you can do so with the DUPNAME option cl gt imcopy fitsfile fits 7 gt gt gt outfile fits append dupname If you need to replace an existing extension with a new output extension you can use the OVERWRITE option as follows Overwriting can cause a lengthy rewrite of the whole file to insert the new extension if its size is not the same as the extension it replaces
185. e _ima fits which is produced by partially processing a raw NICMOS data set through only the first few processing steps of calnica The pipeline processing steps BIASCORR ZOFFCORR ZSIGCORR MASKCORR NOISCALC NLINCORR DARKCORR and BARSCORR should be performed before running biaseq but not FLATCORR UNITCORR or CRIDCALC i e the image should not be flatfielded and should be in units of counts not counts per second The nicpipe task in the stsdas hst_calib nicmos package provides a convenient way to carry out the partial calnica processing needed as preparation for biaseq see example below and also section 5 1 The biaseq task assumes that the astronomical signal sky plus sources accumulates linearly with time and that any non linear behavior is due to changing bias levels that are constant within each array quadrant except perhaps for bias jumps If these assumptions are not correct then the task may not work properly E g if the sky background is changing with time either because it is dominated by variable thermal emission or because of scattered earthlight see section 4 8 then the routine may not function correctly The nicmos task pstats may be used to compute and graph data Statistics versus time or readout number which can help to identify time varying background levels Objects which saturate the NICMOS array will also no longer accumulate signal linearly with time However in this case unless a large fraction of the pi
186. e All are located in the calibration package hst_calib nicmos The tasks in the toolbox imgtools mstools package are particularly useful for working with individual STIS and NICMOS imsets See Working with STIS and NICMOS Imsets in chapter 3 of the HST Introduction if you are not familiar with these tasks Below we describe a few tasks of specific interest to NICMOS observers For additional details and examples of these and other tools please refer to the online help Occasionally the STScI NICMOS group introduces new software tasks outside the time frame of major new STSDAS releases These are made available as a separate add on package called nicproto and are usually announced in the STScI Analysis News STAN which is periodically distributed by e mail for more information see section 1 1 This package can be obtained from the STSDAS or STScI NICMOS group WWW sites Tasks in nicproto are generally somewhat experimental and final versions migrate into the hst_calib nicmos package in the next major STSDAS release All routines described in this edition of the handbook are now available in the most recent STSDAS distribution v2 3 ndisplay and markdq The markdq task reads the data quality DQ array from a NICMOS image and marks the DQ flags on the displayed image Each flag value can be set independently to a different color or can be turned off The ndisplay STSDAS Software HJ NICMOS 5 3 task combines the capabilities of th
187. e about which you want help Wildcards are supported For example to display the on line help for the STSDAS mkmultispec task you would type fi gt help mkmultispec 2 There is an optional paging front end for help called phelp For more information type help phelp from within IRAF APP A 8 lf Appendix A IRAF Basics Figure A 3 Displaying On line Help 7 STSDAS MKMULTISPEC Apr93 gt stsdas hst_calib ctools MKMULTISPEC lt Apr93 gt NAME mkmultispec Create a MULTISPEC WCS based on wavelength tables USAGE mkmultispec input wave output DESCRIPTION This task takes input spectra and wavelength tables uses the IRAF curfit routines to fit the wavelength table creates a MULTISPEC world coordinate system WCS description of the fit and creates a new copy of the input spectrum with the new WCS This task is intended to be used with the Hubble Space Telescope HST spectrographic data from Faint Object Spectrograph FOS and Goddard High Resolution Spectrograph lt GHRS to merge the wavelengths that result from the calibration into the data itself so that other IRAF tasks such as splot may be used However quit d downhalf f sp downfull jlcr downline N next ll Available Commands Space Display Next Page Two STSDAS tasks that display only certain sections of the help file are also available e examples Displays only the examples for a task e describe Displays only the descri
188. e obsolete tables ctio images plot utilities dataio imcenv proto vol dbms language rvsao xray digiphotx lists softools Available Packages and Tasks To quit an IRAF session 1 Type logout A 2 IRAF Basics This section describes basic IRAF techniques such as e Loading packages below e Running tasks and commands e Getting online help e Viewing and setting parameters see appendix section A 2 4 Appendix A IRAF Basics J APP A 5 e Setting and using environment variables see section A 2 5 e File management e Troubleshooting A 2 1 Loading Packages In IRAF jargon an application is called a task and logically related tasks are grouped together in a package Before you can use a task you must load the package containing that task To load a package type the name of the package The prompt will then change to the first two letters of the package name and the screen will display the names of all the newly available tasks and subpackages Even though the prompt has changed previously loaded packages remain loaded and all their tasks remain available Note that the standard way to specify a path through the IRAF package hierarchy to a task in a particular subpackage is to separate the package names with periods e g stsdas hst_calib foc focgeom newgeom Figure A 2 Loading Packages Q Type Name of Package to Load L Names Followed by Dot are Pack
189. e the absolute charge in each pixel and the appropriate linearity correction Detector Nonlinearity Issues J NICMOS 4 23 for that charge level The optional calnica parameter zsthresh controls a threshold above which the ZSIGCORR correction is made If you have observed very bright targets you should read the calnica documentation concerning ZSIGCORR Pipeline processed data that were retrieved from the STScI Archive before November 1997 has no ZSIGCORR correction When reprocessing such data the current version of calnica will automatically apply this step to all MULTIACCUM mode observations if both ZOFFCORR and NLINCORR are also being performed 4 3 3 Uncorrected Saturation Occasionally for reasons which are not fully understood NICMOS MULTIACCUM images of bright targets will saturate at an ADU level which is below the nominal saturation threshold specified in the nonlinearity calibration reference file This could happen for example when the variable quadrant bias levels pedestal are at unusually large values When this happens the accumulating counts vs time for the affected pixels level out at the saturated value However because the saturation flag is not set at the NLINCORR stage of calnica when the CRIDCALC step fits up the ramp of counts vs time to determine the count rate slope it does not know to exclude the saturated data values and fits a linear slope to a highly nonlinear data set Among other unp
190. e there is no blooming along the detector array columns as there is with a CCD One way to get a high quality PSF for subtraction is to measure an isolated bright unsaturated star in the same image or to construct a composite PSF using good stars in the image This can be accomplished using the IRAF digiphot package as described in A User s Guide to Stellar CCD photometry with IRAF A PSF obtained from the same image 4 This and other relevant IRAF documents can be obtained from the IRAF Web site at http iraf noao edu NICMOS 5 24 Chapter 5 Data Analysis ensures that effects of telescope focus and pointing jitter on the image quality are properly taken into account In particular this approach will take care of the breathing effect variations of focus position due to thermally induced mechanical displacements in the HST optical path One disadvantage of this method however is that it is difficult to account for positional variations in the PSF over the field of view of the NICMOS cameras see discussion in section 5 3 3 and also in Suchkov amp Galas 1998 NICMOS ISR 98 005 Although these variations do not have a large affect on NICMOS aperture photometry they can be large enough to cause problems for PSF matching and subtraction If no suitable star can be found in the image one can resort to a synthetic PSF computed using TinyTim Figure 5 2 NIC1 Image with PSF Radial Profile Image of Star Taken with NIC1 F165M PSF Ra
191. e which you can print to the screen by typing 1 calcphot result at the IRAF prompt Please see the Synphot User s Guide for more details on this package and see appendix A for information on getting the synphot dataset which is not included with STSDAS 3 4 Displaying HST Spectra 3 4 1 This section shows how to plot your HST spectra for a quick first look and how to generate hardcopies of your plots Because the STIS data format differs from that of FOS and GHRS we will discuss STIS data separately FOS and GHRS Spectra Before you work with FOS and GHRS data within STSDAS you will want to convert the FITS files you received from the Archive into GEIS format see section 2 3 1 for instructions After conversion the c1h file will hold the calibrated flux values for each pixel the cOh file will hold the corresponding wavelengths and the c2h file will hold the propagated statistical errors Each group of an FOS or GHRS GEIS file contains the results of a separate subintegration FOS readouts taken in ACCUM mode are cumulative so the last group contains the results of the entire integration In contrast GHRS readouts and FOS readouts in RAPID mode are independent If you want to see the results of an entire GHRS FP SPLIT integration you will need to align and coadd the spectra in the groups of the GHRS file You can also combine all the groups in an FOS or GHRS data file without wavelength alignment using the recombine task
192. e C 3 Choosing Observation Log Files in StarView HST RetrievalConfigurations Options STScI Archive Username Note Calibrated and Uncalibrated m requests are now bundled into one option STScI Archive Password Both will be delivered WFPC2 NICMOS and STIS calibrations v Remember Password are now all done with OTFR New Account g Change PW X Select the data type s for retrieval Choose a method of data delivery Q Calibrated amp Uncalibrated Data Net Network Internet Best Reference Files Used Reference Files Host Archive Host FTP v Observation Log Files Data Quality Tape Exabyte Tape Show Override Options Expert Tape Dat Tape Done X Clear f Cancel he APP C 10 Appendix C Using Observation Logs C 3 Using Observation Logs Here are some simple examples of what can be learned from the observation log files Note that for FITS format observation logs current versions of STSDAS tools will handle the files with extensions properly Keywords can be viewed with tools such as imheader or hedit and data viewed plotted or displayed using the same tasks one might have for the GEIS files For more information on FITS file structures see chapter 2 of the HST Introduction C 3 1 Guiding Mode Unless requested all observations will be scheduled with FINE LOCK guiding which may be one or two guide stars dominant and roll The spacecraft may roll slightly durin
193. e IRAF task display and the task markdq it displays a NICMOS image and overlays the DQ flags according to a user specified color code Both tasks are useful for locating specific DQ values for example the cosmic rays rejected by calnica in a MULTIACCUM image mosdisplay The mosdisplay task provides a convenient way to display images from all IMSETS of a NICMOS MULTIACCUM image together as a mosaic in a single ximtool or saoimage window The user may select which extension e g SCI ERR TIME SAMP or DQ to display and can control the display threshold parameters or leave them to be automatically determined pstack and pstats The pstack and pstats tasks plot all the samples of a specified pixel or image section respectively from a NICMOS MULTIACCUM image as a function of time These tasks can be used to track the time behavior of an image on a pixel by pixel basis For example the temporal positions of cosmic ray hits or the onset of saturation during the course of an exposure can be located for a defined set of pixels The pstats task can be particularly useful for identifying anomalous data behavior such as drifting bias levels or scattered light which may cause the background level to vary substantially during the course of an exposure sampinfo The sampinfo task offers a convenient way to get readout by readout information about a NICMOS MULTIACCUM image It provides information about the overall readout sequence SAMP_SEQ NEXTEND
194. e bottom edge of the field of view for all 3 cameras looks at a black mask on the FDA This means that there is less signal from the telescope along that edge and thus the throughput is decreased In NIC3 15 rows along the bottom edge are severely affected and the throughput there ramps down steeply to about 30 of the mean for the rest of the array For NIC2 it has about the same extent but is only reduced to 95 of the mean of the rest of the array The effect for NIC1 is even smaller This hard edge moved around slightly with time and thus does not flatfield away perfectly especially for camera 3 where the gradient is steep Because the vignetting is small for cameras 1 and 2 the resulting flatfielding uncertainty is generally negligible The coronagraphic hole in camera 2 is also on the FDA so its motions correlate with those of the vignetted region In addition the NICMOS cameras also imaged part of the forward bulkhead at the entrance aperture This warm metal surface emits radiation in the longer wavelength bands This emission extends over about 50 rows in NIC3 and about 20 rows in NIC2 Moving the Field Offset Mechanism FOM causes NICMOS to see a different part of the sky in the HST focal plane and essentially to look farther away from the bulkhead that causes the emission This FOM repositioning was automatically implemented for all camera 3 observations from January 1998 the first NIC3 refocus campaign onward so data taken aft
195. e columns rows avoiding regions affected by bright or extended targets and subtracting the median values from each column or row of the data This can at least provide a cosmetic fix In principle this correction should probably be applied before flatfielding the images since it is most likely that the Staypuft signal is not responding to the array QE variations although this has not yet been formally tested However if the fit is done before flatfielding then the sky background itself will not be uniform and in fact will be improperly subtracted by the procedure For this reason in practice it is probably safer if not strictly correct to apply a median column or row for NIC1 correction after flatfielding instead The STScI NICMOS group is now experimenting with algorithms to correct the Staypuft column row effect in NICMOS 4 36 Chapter 4 Anomalies and Error Sources 4 6 4 post processing based on an empirical model for its electronic behavior A software tool for correcting data may be released sometime in the future and it is possible that the procedure may be automatically implemented as a step in the calnica pipeline Optical Ghost Images In addition to persistence and electronic ghosts NICMOS polarimetric images of bright targets are subject to optical ghosts figure 4 10 These are most evident for the short wavelength polarizers in NIC1 The location of the polarizer ghosts relative to the source changes direction
196. e data files output from calnica and requires associa tion tables _asn fits andthe spt fits files Both tasks determine which calibration steps are to be performed by looking at the values of the calibration switch keywords in the primary header of the input science data files see table 2 3 The tasks select the reference files to use in the calibration of the data by retrieving the reference file names from the reference file keywords also located in the primary header of the input data files The appropriate values of the calibration switches and reference file keywords depend on the instrumental configuration used the date when the observations were taken and any special pre specified constraints They are set in the headers of the raw data file in the pipeline during the generic conversion process The calibration indicators keywords record which steps have been performed on the data and get updated after processing In particular the indicators for completed steps will have been assigned the value PERFORMED while the indicators for the steps that were not performed will have been set to OMITTED or SKIPPED The calibration indicators keywords should be examined in the primary header of the calibrated science data _cal fits to determine what calibration steps were applied to the data The calnica and calnicb tasks are available in STSDAS in the hst_calib nicmos package By using these tasks observers can recali
197. e for a given detector and filter or polarizer combination Error estimates and DQ flags contained in the FLATFILE are propagated into the processed images There is one FLATFILE per detector and filter combination UNITCORR Convert to Count Rates The conversion from raw counts to count rates is performed by dividing the science SCI and error ERR image data by the exposure time TIME image data No reference file is needed Basic Data Reduction calnica IJ NICMOS 3 15 PHOTCALC Photometric Calibration This step provides photometric calibration information by populating the photometry keywords PHOTMODE PHOTFLAM PHOTFNU PHOTZPT PHOTPLAM and PHOTBW with values appropriate to the camera and filter combination used for the observation The photometry parameters are read from the PHOTTAB reference file which is a FITS binary table containing the parameters for all observation modes The values of PHOTFLAM and PHOTFNU are useful for converting observed count rates to absolute fluxes in units of erg s em Angstrom or Jy respectively see section 5 3 PHOTCALC does not alter data values which remain in units of counts or counts per second but simply populates header keywords with the appropriate calibration information CRIDCALC Cosmic Ray Identification and Signal Accumulation This step identifies and flags pixels suspected of containing cosmic ray CR hits For MULTIACCUM mode observations this step also combines the da
198. e g Fowler and Gatley 1990 ApJ 353 L33 In practice actual noise reduction in NICMOS observations is generally rather less than Vn for a variety of reasons such as amplifier glow see section 4 1 1 The supported NREAD values are 1 and 9 BRIGHTOBJ The BRIGHTOBJ BRIGHT OBJect mode provides a way to observe objects that would usually saturate the detector in less than the minimum available exposure time which is the amount of time it takes to read out the array and is 0 203 seconds In BRIGHTOBJ mode each individual pixel per quadrant is successively reset read integrated for a time requested by the observer and read again and then these steps are performed for the next pixel in the quadrant The returned image contains the number of counts accumulated between the initial and final reads for each pixel Gust like ACCUM mode Since each quadrant contains 16 384 pixels the total elapsed time to take an image in this mode is 16 384 times the requested exposure time for each pixel BRIGHTOBJ mode was rarely used for on orbit science observations and is essentially uncalibrated In Cycle 11 BRIGHTOB is an avail able observing mode for the special case of acquisition of very bright targets for coronagraphy but is not supported by STScI RAMP RAMP mode was designed to use multiple non destructive reads during the course of a single exposure much like MULTIACCUM but only a single image is sent to the ground Although RAM
199. e ordinarily BACKEST1 has value 0 0 and in this case the background value computed by calnicb is always used unless the user has manually set BACKEST1 to some non zero value 3 The global constant background signal is computed by taking the mean of the background values for each image again using iterative sigma clipping to reject outliers 4 The final mean background value is subtracted from all images both target and background images if present 5 With dither only patterns the user has the option of subtracting the individual background values computed for each image from them selves rather than computing and subtracting a global mean back ground value This option is controlled by the meanbkg task parameter for calnicb The default value yes indicates that the global mean is to be used Mosaic Construction Mosaic MOS images are created for each independent pointing within the pattern For example a combination DITHER CHOP pattern will produce one mosaic image out of the dithered pattern at each CHOP location on the sky Each mosaic image is created as follows 1 The relative offsets between images within the mosaic are computed from their WCS information and refined using cross correlation as in the case of multiple exposures at each pattern position see Com bination of Multiple Exposures on page 3 20 The first image in the list for each mosaic is used as a reference image 2 An empty mosaic image i
200. e position for any single star in your HST image then your absolute astrometric accuracy will be limited only by the accuracy with which you know that star s location and the image orientation If there is a star on your image suitable for astrometry you may wish to extract an image of the sky around this star from the Digitized Sky Survey and measure the position of that star using for example the GASP software described in the STSDAS User s Guide These tools provide an absolute positional accuracy of approximately 07 7 Contact the Help Desk for assistance send E mail to help stsci edu INTRO 3 12 Chapter 3 STSDAS Basics 3 3 2 Examining and Manipulating Image Data This section describes implot and imexamine two basic IRAF tools for studying the characteristics of an image and table 3 3 lists some useful IRAF STSDAS tasks for manipulating images implot The IRAF implot task in the plot package allows you to examine an image interactively by plotting data along a given line x axis or column y axis When you run the task a large number of commands are available in addition to the usual cursor mode commands common to most IRAF plotting tasks A complete listing of commands is found in the on line help but the most commonly used are listed in table 3 2 Figure 3 4 shows an example of how to use the implot task Table 3 2 Basic implot Commands Keystroke Command Display on line help Plot a line Plot a
201. e type of data files associated with the dataset s to be retrieved and for the method of delivery of these files The options for type of file include files calibrated with the On The Fly Recalibration OTFR pipeline for the WFPC2 NICMOS STIS and ACS instruments OTFR applies the best available calibration files i e dark current and flat field images taken closest in time to the observations to the uncalibrated data files You may also request the uncalibrated raw files and calibration files separately For some of the earlier instruments e g WFPC and FOS you may request both the calibration files actually applied to the images as well as those that should provide the best calibration of them if recalibration is desired You may also request Data Quality and Observation Log files Options for data delivery include ftp transfer by the user from the HDA staging disk automatic transfer from the HDA via the Internet to a directory specified by the user and the mailing of tapes or disks If Internet delivery is specified you will be queried for the name of the computer and directory in which the files are to be placed as well as your user name and password on that computer these requests are encrypted so there is no danger of your login information being stolen Upon final submission of the request you will receive an e mail message acknowledging its receipt and another message after all the requested files have been transferred The
202. ects of Overexposure J NICMOS 4 33 Figure 4 8 Cosmic ray persistence in three dithered NIC2 MIF1024 images For each image the histogram at bottom shows the distribution of pixel values near the sky level The shoulder of positive values for the persistence impacted images demonstrates the non Gaussian nature of CR persistence noise The normalized RMS is the measured value divided by the mean for many clean images free of CR persistence Target Galaxy Good negligible CR persistence Bad significant CR persistence Ugly severe CR persistence Normalized RMS 1 004 Normalized RMS 2 452 Normalized RMS 3 108 NOAO IRAP V2 NOA0 RAF 09 Jan 98 NOAO TRAF V2 B 0et 19 From f i TEE E Dia i m AAE EA TANNE wie o Hol ulna z 2 a 2 2 1 o a Cures If you have multiple exposures within a given SAA impacted orbit the amplitude of the persistence should decay and you may want to give later exposures higher weight when combining them Sometimes it may be preferable to discard the worst frames altogether Well dithered data lessens the impact of persistence since objects will move relative to the persistent CR signal and it will not sum coherently when the data are registered With well dithered data at least three positions one can also take advantage of the drizzling procedure and associated software in the STSDAS dither package to identify and mask the worst effects of
203. ed by the integration time The difference between the final and the zeroth readouts is computed on board and the resulting image is sent to the ground In this form the ACCUM mode produces data very similar to the more familiar CCD images A variation to this basic operation is available which replaces the single initial and final readouts with multiple initial and final readouts After the initial reset pass n non destructive reads of the detector immediately follow as close together in time as allowed by the detector electronics The average of the n values is stored as the initial value for each pixel At the end of the integration there are again n NICMOS 1 6 W Chapter 1 Instrument Overview 1 2 3 1 2 4 non destructive readouts with the final value for each pixel being the average of the n reads The number n of initial and final reads is specified by the observer and is recorded in the value of the NREAD number of reads header keyword in the science data files The returned image is the difference between the averaged final and initial values The integration time is defined as the time between the first read of the first pixel in the initial n passes and the first read of the first pixel in the final n passes The advantage of the multiple initial and final MIF readout method is that in theory the read noise associated with the initial and final reads should be reduced by a factor of Vn where n is the number of reads see
204. ed to the exposure time of the science data as is done with most conventional CCD data Each science file must be calibrated with a dark frame of equal exposure time and number of readouts Because there is such a large variety of NICMOS MULTIACCUM readout sequences it was considered to be impractical to obtain and regularly monitor darks in every possible sequence However most components of the NICMOS bias and dark current are highly reproducible and can be reliably calibrated On orbit darks obtained during SMOV and NICMOS 4 4 Chapter 4 Anomalies and Error Sources 4 1 1 throughout the lifetime of the instrument have been used to characterize the dependence of the major dark and bias components on pixel position on time and on temperature for each of the three NICMOS detectors This information has been used to construct synthetic dark calibration reference files for all MULTIACCUM readout sequences using as basic data the on orbit darks obtained during the first part of the Cycle 7 calibration program These are described in section 4 1 3 below Unfortunately some components of the NICMOS bias have turned out to be unstable or unpredictable making it difficult or impossible to remove them using the standard reference files In order to do a good job removing additive dark and bias signatures it is important to understand their origin and behavior Here we describe the various components of NICMOS biases and darks in some detai
205. eeeee 4 21 4 3 2 Non Zero zeroth Read Correction for Bright SOUlCOS 3 ccais ox cen cpiesacecccveehieeussel cedecwsesesesesebehees 4 22 4 3 3 Uncorrected Saturation cccccsscccceeeeeeeeeeeeees 4 23 4 4 PIAA Gh cele ccikg sicertesa edness Sahota aioe ea rnedabaaabentesgeieede 4 24 4 4 1 Characteristics of NICMOS Flatfields 4 24 4 4 2 Temperature dependent Flatfields 0006 4 25 4 4 3 Color Dependence of Flatfields cee 4 25 4 5 Pixel Defects and Bad Imaging Regions 4 26 4 5 1 Hot Pixels Cold Pixels and Grot eeee 4 26 4 5 2 Erratic Middle Column ROW ccccccccccceeeeeeeeeees 4 28 4 5 3 Coronagraphic HoOle ecceeeeeeeeeeeeeeeeeeeeeeeeeeees 4 28 4 5 4 VIGMGUING catrervssrcindctesdauesnsiareragictelenctstatpents uagscnudd 4 29 4 6 Effects of Overexposure cccccccceseteeteeeteeees 4 30 4 6 1 Photon Persistence cccceeeeeeeeeeeeeeeeeeeeeeees 4 30 4 6 2 Cosmic Ray Persistence 4 31 4 6 3 Amplifier Ringing The Mr Staypuft Anomaly ssssssreeeeeeeeeees 4 34 4 6 4 Optical Ghost Images ccceeeeeeeeeeeeeeeeeeeeeeeeees 4 36 4 7 Cosmic Rays of Unusual Size 4 37 4 8 Scattered Earthlight 0 ccccceeeeeeeeeeeeeeeeeees 4 39 Table of Contents W vii Chapter 5 Data Analysis 5 1 5 1 STSDAS Software ccccccsseesesssssesseseeeeeeeeeaees 5 1 5 2 The NICMOS History Tool
206. ell OTFR goes back to the original telemetry the POD files to reconstruct FITS files and then processes these raw FITS data through the most up to date version of the OPUS pipeline software using the latest and best reference files available at the time of retrieval from the Archive As with all HST instruments the pipeline software and reference files have evolved and improved with time as our knowledge of the instrument and its calibration have developed OTFR ensures that users will receive the best standard processing available at the time they request NICMOS data from the Archive and makes it easy to recalibrate data taken earlier in the mission lifetime All of the steps performed by the pipeline are recorded in the trailer file for your dataset _trl fits The main steps performed by the pipeline are 1 The data are partitioned separated into individual files e g engineering and science data are separated 2 The data are edited if necessary to insert fill values in place of miss ing data 3 The data are evaluated to determine if there are discrepancies between a subset of the planned and executed observational parame ters 4 A list of calibration reference files to be used in the calibration of the data is created based on the executed observational parameters This step does not generate comments in the NICMOS trailer file 5 The raw data are converted to a generic FITS format and the header keyword values
207. em e g based on a constant flux per unit wavelength using the photometric zero point keyword PHOTZPT 21 1 simply by m 2 5log PHOTFLAM x CR PHOTZPT 2 5log PHOTFLAM x CR 21 1 Photometric Calibrations IJ NICMOS 5 9 where CR is the count rate in units of DN sec On the other hand the magnitude in Oke s AB system e g based on a constant flux per unit frequency is obtained by applying the following expression M 2 5log 10 x PHOTFNU x CR 48 6 2 5log PHOTFNU x CR 8 9 As noted above the NICMOS filter bandpasses do not match those of ground based filters and therefore it is not straightforward to derive standard infrared magnitudes normalized e g to the spectral energy distribution of Vega However it may sometimes be useful to approximate a Vega based photometric system by using an estimate of the flux density of Vega through the NICMOS bandpasses as a photometric zeropoint Because there are no direct spectrophotometric observations of Vega or other AOV standards through the NICMOS filter system our best option is to use a spectrophotometric model for Vega and synthetically integrate it through the bandpasses Table 5 1 through table 5 3 give bandpass averaged flux densities in Jy for the NICMOS filters using a model reference spectrum of Vega Colina Bohlin amp Castelli 1996 ISR CAL SCS 008 An approximate Vega normalized magnitude may be computed as m ZP Vega
208. ength values associated with each data value The online help explains a few pieces of additional information that must be included as header lines in an input text file By selecting a combination of functional forms for various components you can fit complex spectra with multiple continuum components blended emission and absorption lines absorption edges and extinction Available functional forms include linear power law broken power law blackbody and optically thin recombination continua various forms of Gaussian emission and absorption lines absorption edge models Lorentzian line profiles damped absorption line profiles and mean galactic extinction 3 6 References 3 6 1 Available from STScl http stsdas stsci edu STSDAS html e STSDAS Users Guide version 1 3 September 1994 e STSDAS Installation and Site Managers Guide version 2 3 June 2001 e Synphot Users Guide December 1998 e IGI Reference Manual version 1 3 October 1992 4 Additional information is available in the Astronomical Data Analysis Software and Systems IIT ASP Conference Series Vol 61 page 437 1994 INTRO 3 38 Chapter 3 STSDAS Basics 3 6 2 Available from NOAO http iraf noao edu docs docmain html e A Beginners Guide to Using IRAF 1993 J Barnes e Photometry Using IRAF 1994 L Wells e A User s Guide to Stellar CCD Photometry with IRAF 1992 P Mas sey and L Davis 3 6 3 Other References Cited in This Chapter
209. ensions FITS File Format W INTRO 2 5 Inherit keywords from the primary header e Append new extensions to existing FITS files Retaining the fits at the end of every FITS file name in your file speci fications will ensure that IRAF both reads and writes these images in FITS format If you want to work with STIS and NICMOS data you will need to upgrade to IRAF 2 11 or higher and STSDAS 2 0 Generating a FITS File Listing Once you have downloaded STIS ACS or NICMOS FITS files from the Archive you may want an inventory of their contents To generate a listing of a FITS file s extensions you can use the catfits task in the tables package The following example in table 2 1 illustrates the first 11 lines generated by catfits from a NICMOS MULTIACCUM FITS file containing images only The first column of a catfits listing gives the extension numbers Note that the primary HDU is labeled extension number zero The second column lists the extension type given by the keyword XTENSION IMAGE image BINTABLE binary table TABLE ASCII table The third column lists the extension name given by the keyword EXTNAME In STIS ACS and NICMOS image files the EXTNAME values SCI ERR and DQ indicate science error and data quality images respectively NICMOS image files contain samples and exposure time images as well with EXTNAME values SAMP and TIME Each STIS or NICMOS readout generates an image set or imset STIS
210. er 0 1 flag Recentering status TakeData 0 1 flag Vehicle guiding status SlewFlag 0 1 flag Vehicle slewing status Appendix C Retrieving Observation Logs W APP C 9 C 2 Retrieving Observation Logs You can retrieve observation log files for data taken after October 20 1994 from the HST Archive using StarView as described in chapter 1 of the HST Introduction Unlike science data which generally has a one year proprietary period observation log files become public as soon as they are archived The easiest way to get OMS files through StarView is to identify the observation of interest and proceed with your request as described in chapter 1 of the HST Introduction until you reach the HST Retrieval Configurations Options screen reproduced in figure C 3 You can then check the Observation Log Files box along with any other desired boxes and continue with your request StarView will then deliver the associated observation log files For observations logged between October 1994 to August 1995 you will be delivered the cmi cmj and cmh files in FITS form e g _cemi fits Observations archived from August 1995 to February 1997 will return jif fits and jit fits files These and the earlier FITS files can be worked with as such or converted to their GEIS counterparts via the STSDAS strfits task However as of February 1997 the jif fits and jit fits files are standard FITS files with extensions and cannot be converted to GEIS Figur
211. er bandpasses do not conform to those of instruments used at ground based observatories Instead its filters were designed to meet the anticipated scientific demands Thus in practice NICMOS does not have filters matched to any of the ground based photometric bands The photometric calibration of NICMOS data is discussed in this section Cases of continuum sources emission lines and grism spectra will be presented Units for NICMOS Photometry Given the multitude of units and systems that have been used for infrared photometry magnitudes Jy W m umt erg sec cm um etc and given the lack of a standard for ground based infrared filters NICMOS has adopted the approach of calibration to physical units i e Janskys Jy or Jy arcsec for surface brightness Details on how to transform different sets of units can be found in Appendix 2 of the NICMOS Instrument Handbook or obtained using the NICMOS Unit Conversion Tool available on the STScI NICMOS web pages Fluxes and Magnitude Zeropoints The NICMOS calibration pipeline provides two photometric parameters for the conversion of countrates into fluxes These parameters are found in the keywords PHOTFNU and PHOTFLAM in the header of the calibrated image The definitions of these keywords are discussed in section 3 3 4 of the HST Introduction Very briefly for NICMOS these are the bandpass averaged flux densities in F for PHOTFLAM or F for PHOTFNU for a source that would produce
212. er that time are unaffected Data in the longer wavelength filters taken prior to that time may have an elevated gradient in the sky background The FOM is forward of the FDA in the optical path so the repositioning has no effect on the FDA vignetting described above NICMOS 4 30 Chapter 4 Anomalies and Error Sources Yy Another consequence of the vignetting is its impact on image shape and geometric distortion for NIC3 images taken out of focus i e at any time outside the two NIC3 refocus campaigns January and June 1998 The vignetting introduces some additional image distortion especially over the first 50 rows of the detector when the camera is out of focus see e g Cox et al Instrument Science Report OSG CAL 97 07 Users should regard astrometry and PSF shape in that portion of non campaign NIC3 images with some caution Cures For camera 3 data it may be prudent to discard data from the bottom 10 to 15 rows At the very least photometry in that region should be treated with suspicion Data taken prior to the FOM repositioning in January 1998 may have elevated background gradients for camera 3 For NIC3 images taken outside of the refocus campaigns image shape and astrometry over the bottom 50 rows should be regarded with cau tion 4 6 Effects of Overexposure 4 6 1 Because each pixel of the NICMOS detectors is read individually overexposure does not cause bleeding along columns or rows as is seen w
213. erture which has the aperture fiducial point at the image position of the coronagraphic hole on NICMOS 5 30 Chapter 5 Data Analysis the detector The science exposures are then specified using any of the NICMOS observing modes and any of the NIC2 filters The various modes of NICMOS coronagraphic acquisition and the processing required to analyze the resulting data are described in detail in a series of Instrument Science Reports ISRs by Schultz et al which are available from the STScI WWW pages Users analyzing coronagraphic data or planning future coronagraphic observations should carefully read NICMOS ISR 031 ISR 98 012 ISR 98 019 and ISR 99 006 Some important highlights for understanding and reducing coronagraphic data are summarized here but the reader should consult the ISRs for more detailed discussions Onboard Acquisition In Mode 2 acquisition see NICMOS ISR 98 012 Schultz et al the onboard NICMOS flight software FSW will locate the position of the coronagraphic hole and target It will use this information to calculate an offset to slew the telescope to position the image of the hole over the position of the target The location of the coronagraphic hole is determined from pointed flat field observations Two short ACCUM F160W filter exposures 7 514 seconds each with calibration Lamp 1 on flat field and two identical exposures with the lamp off background are obtained before the acquisition images The tel
214. escope is NOT slewed to move the target out of the FOV during the lamp on and background observations The image of the target will be superimposed on these images The flight software combines the two background and two flat field images subtracts the background image from the flat field image and determines the position of the hole These temporary difference images are not saved The location of the hole is temporarily stored onboard but it is not included in the science telemetry The target position and the slew are stored within the embedded engineering attached to the data set This information is extracted from the engineering telemetry and written to the ipppssoot_spt image The two flat field images are written to image ipppssoot_rwf fits and the two background images are written to image ipppssoot_rwb fits An error in the Flight Software code prior to June 28 1998 resulted in errors in the determination of the image position of the coronagraphic T hole Usually this error was at the sub pixel level and occasionally was off by a pixel The decentered imaging affected the coronagraphic performance It was corrected after this date Coronagraphic Reductions IJ NICMOS 5 31 The acquisition aperture is a square area on the detector a 128 x 128 pixel aperture center at 157 128 of size 9 6 x 9 6 arcseconds Two ACCUM images of equal exposure are obtained and are saved together in a single fits file A summary of the files pro
215. esign they are generally used only for very bright targets and most sources of dark and bias are probably relatively unimportant compared to the object signal The behavior of the detector bias in BRIGHTOBJ mode has not been systematically characterized at STScI and no DARK reference frames are available for this mode What is Removed by Standard Pipeline Processing The DC bias or reset level is removed from NICMOS images by subtracting the zeroth readout from subsequent readouts For MULTIACCUM data this is accomplished by calnica with the ZOFFCORR step For ACCUM data the zero read subtraction is performed automatically on board the telescope The DARKCORR step of calnica subtracts a dark reference image specified by the DARKFILE header keyword from the science exposure For MULTIACCUM data this is done for each sample readout 1 e imset matching the appropriate imsets of the DARK reference file to those of the science image The DARKFILE includes all three additive components described above i e true dark current amplifier glow and bias shading In general the DARKCORR step of calnica using standard STScI reference files should do an adequate job of removing linear dark current amplifier glow and most shading Cures How To Get Rid of What s Left Several components of the bias may not be adequately removed by the standard pipeline dark correction In particular residual shading in NIC2 NICMOS 4 14 J Chapter 4 Anom
216. esired image S x y is recovered but an additive inverse flatfield pattern is also present with an amplitude that may be different for each quadrant These inverse flat patterns along with discontinuities between quadrants are the typical hallmarks of a pedestal problem in processed NICMOS data see example in figure 4 3 Figure 4 3 Data affected by variable quadrant bias Left image processed nor mally with calnica note the quadrant intensity offsets and also the residual flat field pattern imprinted on the data due to the unremoved bias being multiplied by the inverse flat Right image after processing through pedsky It is important to note here that a residual flatfielding pattern may also arise from reasons completely unrelated to pedestal In particular the NICMOS flat fields have a strong color dependence and the spectrum of the background especially at longer wavelengths where thermal emission dominates does not necessarily match that of the lamps used to create the flat fields Residual patterns may therefore sometimes result from division by standard internal lamp flats again especially at longer wavelengths in the medium and broad band filters We return to this point in section 4 1 5 in the discussion of the pedsky software routine and again in section 4 4 2 Unremoved shading also introduces a bias offset but a positionally dependent one which when multiplied through by the inverse flatfield will create a pedest
217. ession for the Flux above can be directly applied to the first case while a correction factor 1 11 7421 1 6662 2 is needed in the second case Absolute Spectrophotometry with NICMOS Grisms The accuracy of the absolute spectrophotometry with NICMOS grisms depends on three limiting factors e Accuracy of the spectral energy distribution of the standard stars used to obtain the inverse sensitivity curve e Quality of the flat fielding and background subtraction of the calibra tion observations e Quality of the flat fielding and background subtraction of the science observation itself The major source of uncertainty in the absolute spectrophotometry of a given source comes from the variability and structure of the background Every pixel on the NIC3 array will receive background radiation over the entire spectral bandpass of the particular grism while the source spectrum Astrometry Pixel scales and Geometric Distortion J NICMOS 5 19 will be dispersed The accuracy of the background subtraction is limited by our knowledge of the spectral response of each pixel which is somewhat different from pixel to pixel Extracted spectra will have to be corrected for the spectral response of each pixel The accuracy of this correction is again limited by our knowledge of the detector response Remember that the spectra are not aligned with the X axis of the detector and so move from one row to the next This makes grism spectra espec
218. ew CHAPTER 2 Data Structures In this chapter 2 1 NICMOS Data Files 2 1 2 2 Header Keywords 2 10 2 3 Working with NICMOS Files 2 16 2 4 From the Phase II Proposal to Your Data 2 20 2 5 Paper Products 2 22 This chapter is a guide to the structure of NICMOS data The data file naming convention formats and organization are described as are the file header keywords The connection between the Phase II exposure logsheets and the data you receive is also explained together with the available paper products 2 1 NICMOS Data Files STScI automatically processes and calibrates all NICMOS data and archives the data files resulting from pipeline processing in FITS format If you have retrieved NICMOS files from the Archive you will notice that their names look like this n3w2alwqm_cal fits The first part of the file name n3w2alwqm is the rootname identifying the dataset to which the file belongs the second cal is the suffix identifying the type of data the file contains and the third fits indicates that this is a FITS format file Chapter 2 of the HST Introduction shows how to access the data contained in NICMOS FITS files while appendix B of that volume NICMOS 2 1 NICMOS 2 2 Chapter 2 Data Structures 2 1 1 explains how to decipher the rootnames of these files and explains why some of them are grouped into data associations This section describes the files that constitute a NICMO
219. ew from it Enter in to StarView mode by clicking on the StarView button in the lower left hand menu of VTT Clicking on a DSS image will then spawn a Quick StarView screen with the R A and Dec of the position you clicked loaded into the search fields You can enter other constraints into these fields as usual Search results can be displayed on the VTT screen by selecting the results in StarView and pressing the Overlay button Quick Data Retrieval with StarView The following steps summarize the basic process that PIs need to go through to retrieve their data with StarView These steps follow registration as a MAST user notification from STScI that the observations for a given proposal are complete and providing StarView with your e mail information They are intended as a quick reference for this process 1 Start StarView 2 Click the Quick button 3 Enter your PI name and or proposal ID number in the appropriate cell 4 Click the Search button INTRO 1 16 Chapter 1 Getting HST Data 5 Use the Scan button to step through the retrieved files after tog gling the right most button at the bottom of the Results window to Update to verify that all datasets have been retrieved 6 Preview some or all of the datasets if desired to verify data quality and target acquisition 7 Click All to mark all datasets for retrieval or Mark to mark indi vidual datasets for retrieval 8 Click
220. ey are a kind of signal like a slowly decaying highly structured dark current Cosmic ray persistence adds non Gaussian spatially correlated noise to images and can significantly degrade the quality of NICMOS data especially for exposures taken less than 30 minutes after an SAA passage see examples in figure 4 8 Count rates from moderately bad cosmic ray persistence can be of order 0 05 ADU second with large pixel to pixel variations reflecting the spatial structure of the signal The effective background noise level of an image can be increased by as much as a factor of three in the worst cases although 10 to 100 is more typical This noise is primarily due to the spatially mottled structure in the persistence not the added Poisson noise of the persistence signal itself Because HST passes through the SAA seven or eight times a day a large fraction of NICMOS images are affected by cosmic ray persistence to one degree or another Observations of bright objects are hardly affected since the persistent signal is usually quite faint Similarly short exposures are not likely to be badly affected because the count rate from persistence is low and may not exceed the detector readout noise But deep imaging observations of faint targets can be seriously degraded The NICMOS Instrument Science Report SR 98 001 Najita Dickinson and Holfeltz 1998 presents a detailed discussion of this phenomenon and its effects on imaging observations Eff
221. fits a linear function to counts vs time triggering the rejection algorithm for some pixels and not others and resulting in erroneous slope fits and hence incorrect derived count rates for some pixels Cures Fortunately fora MULTIACCUM observation one can take advantage of the time resolved nature of the data to exclude individual readouts where scattered light contaminates the data As an example let us look at one data set where scattered light plays a role In this example we will also use some of the tools in the stsdas hst_calibnicmos package which are described in more detail in chapter 5 First we will partially process the image through calnica using nicpipe skipping the UNITCORR FLATCORR and CRIDCALC steps The resulting _ima fits image is thus in units of counts not countrate Next we use the sampdiff task to plot the median counts in each IMSET of the image vs the sample time ni gt nicpipe n4uxllufq_ raw fits stage biaseq ni gt pstats n4uxllufq_ima fits gt gt gt extname sci units counts stat midpt The result is shown in figure 4 12 NICMOS 4 40 Chapter 4 Anomalies and Error Sources Figure 4 12 Plot of median counts vs time for readouts from a NICMOS image The upturn in the last few readouts shows the effects of scattered light NOAO IRAF V2 11 2EXPORT med bathsheba stsci edu Fri 18 21 09 15 Oct 1 n4uxilufq_ima fits sci EE S E EEE See Le Counts DX
222. for removing this variable bias level Here we briefly describe the tools that are currently available in the stsdas hst_calib nicmos package biaseq The biaseq task in the stsdas hst_calib nicmos package is designed to remove the changes in quadrant bias level from readout to readout during the course of a MULTIACCUM exposure It adjusts the bias levels in each NICMOS quadrant so that the net counts in that quadrant increase linearly with time This bias equalization procedure does not remove the net bias offset that produces the pedestal effect Essentially it removes any temporally non linear components of the bias drift i e the second and higher order time derivatives of the bias but leaves an unknown linear term in the bias drift i e the first time derivative The program cannot distinguish between this linear bias drift and an actual linearly accumulating astronomical signal and thus leaves the linear bias term in the data so that it must be removed by some other method see pedsky NICMOS Dark Current and Bias IJ NICMOS 4 15 and pedsub below In principle biaseq will work on any NICMOS MULTIACCUM image regardless of the nature of the astronomical sources present provided that there are enough MULTIACCUM samples available As a by product biaseq can also attempt to identify and remove bias jumps or bands see section 4 1 2 above from individual readouts The biaseq task must be run on an intermediate image fil
223. from one quadrant to another for electronic reasons and flatfielding also introduces variations along the column so that a constant correction derived from the bottom rows may not be appropriate Nevertheless the process results in first order cosmetic improvement and may be worthwhile Persistent afterimages from previous exposures of the target star see section 4 6 1 can also be a problem for coronagraphic images and users should be aware of this effect PSF Subtraction The light distribution within the PSF and the pattern of light scattered about the hole can change significantly on both short and long time scales from orbit to orbit and over the lifetime of NICMOS see section 5 5 for a general discussion of focus and PSF issues These changes may be attributed to several factors including OTA focus variations thermally induced motions in NICMOS fore optics possible changes in the position of the cold mask and coronagraphic hole motion All of these changes are related to either the thermal input to the telescope changes in Sun angle attitude and spacecraft roll or to the dewar thermal short and subsequent cryogen depletion The PSF also varies as a function of position across the field of view which may affect the quality of PSF subtractions see figure 5 8 In addition the HST focus is known to oscillate with a period of one HST orbit Changes in the focus are attributed to thermal contraction expansion of the optical telesc
224. g an observation if only one guide star is acquired The amount of roll depends upon the gyro drift at the time of the observation the location during an orbit and the lever arm from the guide star to the center of the aperture There are three commanded guiding modes FINE LOCK FINE LOCK GYRO and GYRO OMS header keywords GUIDECMD commanded guiding mode and GUIDEACT actual guiding mode will usually agree If there was a problem they won t agree and the GUIDEACT value will be the guiding method actually used during the exposure If the acquisition of the second guide star fails the spacecraft guidance GUIDEACT may drop from FINE LOCK to FINE LOCK GYRO or even to GYRO which may result in a target rolling out of an aperture Check the OMS header keywords to verify that there was no change in the requested guiding mode during the observation Until new flight software version FSW 9 6 came online in September 1995 if the guide star acquisition failed the guiding dropped to COARSE track After September 1995 if the guide star acquisition v failed the tracking did not drop to COARSE track Archival research ers may find older datasets that were obtained with COARSE track guiding The dominant and roll guide star keywords GSD and GSR in the OMS header can be checked to verify that two guide stars were used for guiding or in the case of an acquisition failure to identify the suspect guide star The dominant and roll guide
225. g routines like pedsky Cures A discussion of flat field color dependence is presented in Storrs Bergeron and Holfeltz 1999 ISR NICMOS 99 002 That paper describes methods for constructing color dependent flatfield reference files and provides IRAF scripts for doing so In general when using NICMOS data you should keep in mind the large spatial variations in sensitivity and signal to noise that result from the flat field structure This can have important consequences when you are analyzing NICMOS data requiring e g careful handling when setting source detection thresholds in automatic routines like DAOPHOT or SExtractor or for error analysis on photometry 4 5 Pixel Defects and Bad Imaging Regions 4 5 1 Hot Pixels Cold Pixels and Grot Each NICMOS array has a small number of bad pixels which may be either cold i e very low or zero response or hot i e with very high or erratic dark current Most of these were mapped during thermal vacuum testing and static bad pixel masks are used to set error flags in the ERR arrays during the MASKCORR step of calnica processing The statistics on the cold and hot pixels present in each of the NICMOS cameras are presented in table 4 1 Pixel Defects and Bad Imaging Regions W NICMOS 4 27 In addition to the bad pixels which were already known from ground based testing more pixels have shown low measured quantum efficiency in orbit Now known as grot they appear as small areas of re
226. ght targets imaged by the previous NICMOS observer Figure 4 7 Persistence induced by an exposure of a bright star The left and right images show dark frames taken 32 and 512 seconds after the exposure of the star 32 seconds delay 512 seconds delay Cures There is no easy cure for persistence in existing data just be aware that it may be present For dithered observations you can mask out persistent images from previous exposures before combining into a mosaic It may be possible to subtract a rescaled version of the previous image that caused the persistent afterglow from the persistence image itself and thus remove it see the discussion of cures for cosmic ray induced persistence below Cosmic Ray Persistence More insidiously during regular passages of HST through the South Atlantic Anomaly SAA the arrays are bombarded with cosmic rays which deposit a large signal into nearly every pixel The persistent signal from these cosmic rays may then be present as a residual pattern during exposures taken after the SAA passage This appears as a mottled blotchy or streaky pattern of noise really signal across the images something like a large number of faint unremoved cosmic rays These persistent features cannot be removed by the MULTIACCUM cosmic ray processing done by the standard pipeline i e the CRIDCALC step of calnica NICMOS 4 32 Chapter 4 Anomalies and Error Sources because they are not transient Rather th
227. ght HJ NICMOS 4 41 exposure time in your image but will eliminate the elevated background the uneven illumination and problems resulting from incorrectly fit count rates and accidental triggering of the CRIDCALC cosmic ray rejection This can easily be done by editing the data quality arrays in the DQ extensions of the affected images setting them to some non zero value 4096 is a good choice as it is not otherwise used as a DQ flag value for NICMOS This will cause CRIDCALC not to use those imsets when fitting a slope to counts vs time to derive the count rate You can edit these in the raw data frame and start over with the processing or in the example we are using here in the partially processed frame and then complete the processing using nicpipe For our example we might continue in the following way We want to exclude the last three readouts from further processing Remember that NICMOS imsets are stored in reverse order in the multiextension FITS file i e SCI 1 is the last readout SCI 2 the next to last etc ni gt copy n4uxllufq_ima fits n4uxllufq _imaflag fits ni gt imreplace n4uxllufq imaflag fits DQ 1 4096 ver up ni gt imreplace n4uxllufq imaflag fits DQ 2 4096 ver up ni gt imreplace n4uxllufq_ imaflag fits DQ 3 4096 ver up ni gt nicpipe n4uxllufq_imaflag fits stage final The end product will be called n4duxllufq_imaflag_cal fits and should be free of scattered light albeit with a somewha
228. gnal those below this threshold are ignored The user may set a different zero read detection threshold by using the zsthresh task parameter for calnica The estimated zeroth read signal is then passed on a pixel by pixel basis to the NLINCORR step so that it can account for that signal when applying linearity corrections and saturation checking on the zeroth read subtracted images with which it works The ZSIGCORR step also performs saturation checking on the zeroth and first readout images Note that this technique will not work well for pixels covered by targets that are so bright that the signal is already beginning to saturate in either the zeroth or first readouts Pixels that are determined to have detectable signal in the zeroth read are marked in the DQ images of the output _ima fits file with a data quality flag value of 2048 The ZSIGCORR routine uses the MASKFILE NOISFILE DARKFILE and NLINFILE reference files Basic Data Reduction calnica IJ NICMOS 3 9 The ZSIGCORR routine is implemented in calnica versions 3 0 and higher It was implemented in the standard OPUS calibration pipeline on 11 November 1997 and archived data from before that time does not have the ZSIGCORR step applied If you are concerned about accurate flux measurements for bright sources in NICMOS observa tions taken before that time you may wish to reprocess the data using the latest version of calnica see section 3 5 or to retrieve the data again fro
229. hapter 2 Data Structures holds an integer 16 bit image containing the data which populates the spt fits header keyword values One example of useful information from the support files is detector temperature information which can be important when matching DARK reference files to the images see e g section 4 1 3 Trailer File The trailer files _tr1 fits contain information on the calibration steps executed by the pipelines and diagnostics issued during the calibration There is one _tr1 fits file produced for each dataset and in the case of associations one _tr1 file for each NICMOS product ie each _mos fits file Processing Data Quality File The processing data quality files _pdq fits contain general information summarizing the observation a data quality assessment section and a summary on the pointing and guide star lock They state whether problems were encountered during the observations and in case they were describe the nature of the problem There is one _pdq fits file produced for each dataset and in case of associations one _ pdq file for each NICMOS product i e each _mos fits file 2 2 Header Keywords Both the primary header and the headers of each image extension in a science data file contain keywords The keywords store a wide range of information about the observations themselves e g observing mode integration time filters or grisms used the processing of the data by the OPUS
230. he FITS file infile fits specifically the data from the columns labelled WAVELENGTH and FLUX and will restrict the extraction to the rows where the spectral order SPORDER is within the range 68 70 inclusive Alternatively if you specify infile fits sci 2 c FLUX r row 20 30 IRAF will obtain data from the table stored in the FITS file extension with an EXTNAME of SCI and EXTVER of 2 The data will come from the column FLUX and be restricted to the row numbers 20 30 inclusive Eventually all STSDAS and TABLES tasks will be able to use row and column selection For a complete explanation of the table selector syntax type help selectors 2 3 GEIS File Format The HST specific Generic Edited Information Set GEIS format is the standard format for reducing data from FOC FOS FGS GHRS HSP WF PC 1 and WFPC2 All HST images in GEIS format consist of two components a header file and a separate binary data file both of which should reside in the same directory GEIS header files whose suffixes end in h e g w0100105t clh consist entirely of ASCII text in fixed length records of 80 bytes These records contain header keywords that specify the properties of the image itself and the parameters used in executing the observation and processing the data GEIS binary data files whose suffixes end in d e g wO100105t c1d contain one or more groups of binary data Each group comprises a data array followed by
231. he FSW target position However the hole pattern is not symmetric about the low scatter point pixel with least counts of the OPUS pipeline processed coronagraphic hole image due to the impression of the flat field on top of the image The onboard ACQ background and flat field images need to be reduced in a similar manner as performed by the FSW to achieve a meaningful comparison The coronagraphic acquisition n4q832npq will be used as an example to demonstrate off line processing The background image n4q832npq_rwb fits must be subtracted from the image of the hole n4q832npq_rwf fits and the resulting image flat fielded using a preflight flat or SMOV flat with the hole at a different position In this example the pre flight flat field hls1337dn_fit fits was used to process the hole image The task imcalc is used to combine the pair of background and hole images taking the minimum value at each pixel in order to eliminate cosmic rays gt imcalc n4q832npq rwb01 fits 1 n4q832npq rwb02 fits 1 gt gt gt min_bac min iml im2 gt imcalc n4q832npq rwf01 fits 1 n4q832npq rwf02 fits 1 gt gt gt min _fla min iml im2 gt imarith min_fla min_bac min_flat_bac gt imarith min_flat_bac nref hls1337dn_flt fits 1 gt gt gt pro_flat_bac One can then invert the flat fielded hole image to make the hole positive and then use the IRAF task center to determine the centroid of the reversed hole image The posit
232. he STScI calibration database There are other bad pixels however which you may wish to mask out such as those pixels affected by grot see section 4 1 5 If you wish you can create a new MASKFILE which includes additional bad or suspect pixels and reprocess your data using this new mask BIASCORR Wrapped Pixel Correction NICMOS uses 16 bit analog to digital converters ADCs which convert the analog signal generated by the detectors into signed 16 bit NICMOS 3 10 Chapter 3 Calibration integers Because the numbers are signed and because the full dynamic range of the converter output is used raw pixel values obtained from individual detector readouts can range from 32768 to 32767 DN In practice the detector bias level is set so that a zero signal results in a raw value on the order of 23000 DN In ACCUM and BRIGHT OBJECT modes where the difference of initial and final readouts is computed on board the subtraction is also performed in 16 bit arithmetic Therefore it is possible that the difference between the final and initial pixel values for a bright source could exceed the dynamic range of the calculation in which case the final pixel value will wrap around the maximum allowed by the 16 bit arithmetic resulting in a negative DN value Given the level at which the NICMOS detectors saturate and the analog to digital conversion factor the maximum real pixel value that is expected is on the order of 40000 D
233. he current best estimates of the PHOTFNU and PHOTFLAM values for NICMOS filters These new values update previous numbers given in older versions of the PHOTTAB calibration reference files as well as an interim set of calibrations presented in an earlier edition of this Handbook version 4 0 The new calibrations are believed to be accurate to better than lt 5 thus satisfying the absolute calibration requirements for NICMOS For most filters the relative calibration accuracy should be better lt 3 with the possible exception of some narrow band filters where uncertainties in 1 The PHOTFNU and PHOTFLAM keywords represent photometry corrected to infi nite aperture i e the scaling between stellar flux density and the total count rate mea sured from a star within a hypothetical infinite aperture The actual standard star measurements are made within a fixed finite radius aperture and corrected to infinite aperture using mode point spread functions from TinyTim NICMOS 5 8 Chapter 5 Data Analysis absorption line strengths for the solar analog and white dwarf models may result in greater calibration errors Please note that the NIC1 and NIC2 polarizers have not yet been recalibrated The values given in table 5 1 through table 5 3 are taken from the older PHOTTAB calibration reference file i7112297n_ pht fits and are marked by asterisks Note also that the phtometric calibration for the extremely broad band filters F140W F150
234. he uparm directory will contain your own copies of IRAF task parameters This directory allows you to customize your IRAF 1 Users at STScI should consult the STScI Site Guide for IRAF and STSDAS APP A 4 Appendix A IRAF Basics environment by setting certain parameter values as defaults Once you set up IRAF you should rarely need to do it again expect when updated version of IRAF are installed A 1 2 Starting and Stopping an IRAF Session To start an IRAF session 1 Move to your IRAF home directory 2 Type cl IRAF starts by displaying several lines of introductory text and then puts a prompt at the bottom of the screen Figure A 1 is a sample IRAF startup screen Figure A 1 IRAF Startup Screen Startup Messages Change from Day to Day NOAO Sun IRAF Revision 2 11 Fri Aug 15 15 34 46 MST 1997 This is the EXPORT version of Sun IRAF V2 11 for SunOS 4 and Solaris 2 5 Welcome to IRAF To list the available commands type or To get detailed information about a command type help command To run a command or load a package type its name Type bye to exit a package or logout to get out of the CL Type news to find out what is new in the version of the system you are using The following commands or packages are currently defined apropos euv local spptools ared fitsutil mem0 stlocal aspec focas newimred stsdas e128 ftools noao system color hst_pipelin
235. hen working with FITS files you must specify an extension unless the FITS file contains only a single image in the primary data unit and has no extensions figure 3 2 shows how to display group two of a WF PC 1 image INTRO 3 6 Chapter 3 STSDAS Basics lv_ Tf you want to display all four chips of a WF PC 1 or WFPC2 image y simultaneously you can create a mosaic with the STSDAS wmosaic a task in the hst_calib wfpc package Type help wmosaic for details Figure 3 2 Displaying an Image 5 Run display task cl gt display w0sn0101t c0h 2 from IRAF window frame to be written into 1 4 1 22 237 1182 SAOimage z1 and z2 are image wsn 0tt coht2 SNLSBLV eyes intensity range Image appears in SAOimage window To print hardcopy Click etc 2 Click print Modifying the Display There are two ways to adjust how your image is displayed e Use the SAOimage command buttons that control zooming panning etc e Reset the display task parameters Once an image appears in your SAOimage window you can use the SAOimage commands displayed near the top of the image window to manipulate or print your image The SAOimage Users Guide describes Displaying HST Images IJ INTRO 3 7 these commands although most are fairly intuitive Just click on the buttons to scale pan or print the image or to perform other commonly used functions On line help is also available at the system level t
236. hing criteria such as object name position or proposal number then allow the user to navigate through the set of files matching those criteria and finally to let the user retrieve some or all of the files found in the search Several options for the type of search that can be performed e g by a particular instrument will be discussed later The design of StarView is similar to that of a Web browser At its top are pull down menu bars including File Searches and Help The Help menu offers links to documents including the StarView FAQ page Beneath these menu bars is a row of buttons that run StarView s basic functions such as searching marking files for retrieval and previewing images A Help Getting Data with StarView IJ INTRO 1 5 button allows users to display pop up windows describing the function of the different StarView buttons and windows by first clicking the Help button then the item of interest Beneath the row of buttons is the Qualifications table which is displayed when a search is begun It consists of several cells corresponding to the search parameters the user wishes to use e g object name proposal I D or instrument Below this window will appear the Results table displaying the datasets found to match a given set of search parameters entered into the Qualifications table For the purpose of introduction we will describe the use of the most basic search option called Quick Search which can be started b
237. hits produce unwanted signal in the output images Unlike standard CCD observations however most of the effects of CRs in NICMOS data can be eliminated during data processing thanks to the capability for multiple non destructive readouts in infrared arrays As was described in chapter 3 the calnica processing pipeline identifies cosmic rays in individual readouts of a MULTIACCUM image during the CRIDCALC step and excludes data from that readout when calculating the final count rate for the affected pixel Therefore CRIDCALC processed NICMOS images _cal fits should be free of most or all ordinary cosmic rays The affected pixels will be flagged in the DQ extensions of the _ima fits files It is worth noting that the noise level will be slightly higher for pixels which were impacted by cosmic rays because 1 the effective exposure time for those pixels is shorter because one readout has been discarded 2 breaking the counts vs time ramp fitting procedure into two or more pieces introduces extra statistical noise particularly for observations limited primarily by readout noise and 3 although the cosmic ray signal itself is removed the associated Poisson noise is not Images taken in ACCUM mode have no cosmic ray processing For these you must handle cosmic rays as you would for ordinary CCD images Occasionally NICMOS like other instruments will be hit by a very strong cosmic ray that can affect many pixels figure 4 11 These wi
238. hods for improving your absolute astrometric accuracy Positional Information The header of every calibrated HST two dimensional image contains a linear astrometric plate solution written in terms of the standard FITS astrometry header keywords CRPIX1 CRPIX2 CRVAL1 CRVAL2 and the CD matrix CD1_1 CD1_2 CD2_1 and CD2_2 IRAF STSDAS tasks can use this information to convert between pixel coordinates and RA and Dec Two simple tasks that draw on these keywords to relate your image to sky coordinates are e disconlab Displays your image with a superimposed RA and Dec grid Simply open an SAOimage window and type for example sd gt disconlab n3tc0Ola5r_cal fits 1 e xy2rd Translates x and y pixel coordinates to RA and Dec The task rd2xy inverts this operation SAOimage displays the current x y pixel location of the cursor in the upper left corner of the window To find the RA and Dec of the current pixel you supply these coordi nates to xy2rd by typing sd gt xy2rd n3tcOla5r_cal fits 1 x y Table 3 1 lists some additional tasks that draw on the standard astrometry keywords Observers should be aware that these tasks do not correct for geometric distortion Only FOC images currently undergo geometric correction during standard pipeline processing the cOh c0d and clh cld FOC images have been geometrically corrected STIS images will be geometrically corrected in the pipeline once suitable calibration file
239. iable on its own line The show command with no arguments prints the names and current values of all environment variables A 2 6 File Management This section describes e File formats commonly used with STSDAS and IRAF e Specification of file names e Navigation through directories Appendix A IRAF Basics IJ APP A 13 File Formats IRAF recognizes a number of different file structures Among them are the standard HST file formats known as GEIS and FITS see chapter 2 of the HST Introduction both of which differ from the original IRAF format OIF GEIS is closer to OIF in that two files are always used together as a pair e A header file which consists of descriptive information IRAF header files are identified by the suffix imh GEIS header files are in ASCII text format and are identified by the suffix hhh or another suffix ending in h such as cOh or q1lh A binary data file consisting of pixel information IRAF data file names end with a pix suffix STSDAS data files end with an suffix of hhd or another suffix that ends with d such as cOd or q0d STSDAS always expects both component files of a GEIS image to be kept together in the same directory A single FITS file contains both the header information and the data When working with IRAF or STSDAS images you need only specify the header file name the tasks will automatically use the binary data file when necessary File Specification
240. ially sensitive to the intrapixel sensitivity variation The NICMOSlook software see section 5 8 version 2 7 4 and higher has a capability built in to correct for this variation It depends critically on the placement of the spectrum however and the software handbook describes an iterative procedure to determine the best correction for this problem The absolute flux calibration of the spectral energy distribution of the standard stars in the 0 8 to 2 5 um wavelength range is known to 2 5 Characterization of the grisms absolute sensitivity during SMOV indicates that the absolute calibration of grism spectrophotometry for bright sources i e well above background will have a total 20 30 uncertainty For Grism C the uncertainties could be even higher because of the large thermal background in this wavelength range 1 4 to 2 5 um Grism data reduction and calibration are discussed in more detail in section 5 8 5 4 Astrometry Pixel scales and Geometric Distortion 5 4 1 Accurately transforming pixel positions in NICMOS images to relative or absolute astronomical coordinates involves several considerations Here we consider each of these in turn Pixel Scale Time Dependence The distortion of the NICMOS dewar due to the cryogen expansion affected the optical path pushing the cold well and cameras closer to the field divider assembly and cold mask This caused the effective focal length and hence the pixel scale to change somewhat
241. iation rootname and coordinates and those of the individual exposure APP B 6 lf Appendix B Associations Figure B 1 Association Results Screen from StarView File Searches Constraint View Retrieve Customize Options Comments Help Association ID 38211010 Proposal ID 862 PI last name WAYNE BAGGETT Pattern sree a sposmnnnnnneneonnnnnnoneneoennnnnroneannninnraei Member Name 1N3S211010 Target Name TARGET1 Member Type PROD TARG Start Time 03 29 97 06 16 52 RA RA 2000 17 59 09 185 Dec Dec 2000 i 61 35 02 000 EEE i pararent P Camera 2 Orient 50 364 Aperture Exp Len 127 424 Numpos Nread prove Filter F110W Offset Nsamp prnveenereneneavnrevnvevnerenvne Mode ACCUM Dither Size poreeenrevnveenerenerenvneevnvew Readout FAST prrevrereveeneneenenenvrenene Samp Seq i Chop Size EXPOSURES Dataset Name iN3S21106R Position i Exp Start i Exp Flag H RA RA 2000 18 00 00 000 Dec Dec 2000 i 61 30 00 000 Step Forward Step Back d Mark Dataset Retrieve Marked Data d Scan Forward i Scan Back i Unmark Data Write Result to File i Edit Search Constraints wd Mark Al att View Result as Table it Record 1 of 1 Cin progress Unmark Aq Strategy i Preview overlay Exit Screen Z More re Jabte us cerd controls te view search r J APPENDIX C Observation Logs In this appendix
242. ic image is with the imealc task im gt imcalc x2ce0502t clh x2ce0502t hhh log10 im1 1 0 If the peak pixel in your original image contained 2000 counts for example you would then display the logarithmic image with z1 0 and Z2 3 3 Otherwise the user can simply do im gt display x2ce0502t clh ztrans log 1 Type help display within IRAF to obtain more information about these parameters INTRO 3 8 Chapter 3 STSDAS Basics 3 2 2 The image display buffer can also be adjusted in IRAF by setting the stdimage parameter For example im gt set stdimage imt 2048 will allow a larger image to be displayed without losing the borders Working with Image Sections Sometimes you may want to display only a portion of an image using the syntax for specifying image sections discussed in chapter 2 Your specified pixel range should give the starting point and ending point with a colon separating the two List the horizontal x axis range first followed by the vertical y axis range For example to specify a pixel range from 101 to 200 in the x direction and all pixels in the y direction from group three of a GEIS format image tv gt display image hhh 3 101 200 1 To specify the same pixel range in the second SCI extension of a NICMOS FITS image tv gt display image fits sci 2 101 200 1 If you specify both a group and an image section of a GEIS file the group number m
243. ich require special care on the part of the user Chapter 4 also discusses recent updates to the dark reference files available from 7 STScI including the new dark generator WWW tool Proper removal of additive instrumental signatures i e dark and bias can be one of the most important steps in achieving high quality science grade NIC MOS data reductions and we recommend that the user read the rele vant sections of chapter 4 in detail NLINCORR Linearity Correction The linearization correction step corrects the integrated counts in the science image for the non linear response of the detectors The observed response of the detectors can conveniently be represented by 2 regimes e At low and intermediate signal levels the detector response deviates from the incident flux in a way that is correctable using the following expression F c c xF xF xF e where c c2 and c3 are the correction coefficients F is the uncor rected flux in DN and F is the corrected flux In practice the coeffi cient c4 is set to 1 so that the total correction increases from a value of 1 starting at the zero signal level Basic Data Reduction calnica IJ NICMOS 3 13 e At high signal levels as saturation sets in the response becomes highly non linear and is not correctable to a scientifically useful degree the saturation level is about 30 500 DN with a standard devi ation of about 2 000 DN The NLINCORR step applies the linearity
244. icitly if you want to assign them values different from those in the input HDU You can also specify the FITS File Format Hi INTRO 2 11 OVERWRITE option if you want the output table to supplant an existing FITS extension For example you could type tt gt tcopy n3tc01010_asn fits out fits 3 asn 2 overwrite This command would copy the table in the first extension of n3tc01010 asn fits into the third extension of out fits while reassigning it the EXTNAME EXTVER pair asn 2 and overwriting the previous contents of the extension Note that overwriting is the only time when it is valid to specify an extension EXTNAME and an EXTVER in the output specification Specifying Arrays in FITS Table Cells A standard FITS table consists of columns and rows forming a two dimensional grid of cells however each of these cells can contain a data array effectively creating a table of higher dimensionality Tables containing extracted STIS spectra take advantage of this feature Each column of a STIS spectral table holds data values corresponding to a particular physical attribute such as wavelength net flux or background flux Each row contains data corresponding to one spectral order and tables holding echelle spectra can contain many rows Each cell of such a spectral table can contain a one dimensional data array corresponding to the physical attribute and spectral order of the cell In order to analyze tabular spectral data with
245. ide flowcharts and descriptions of the NICMOS pipeline calibra tion steps and e explain how to recalibrate your data using the calibration software in STSDAS The next chapter chapter 4 will discuss a variety of NICMOS data anomalies which may require processing that goes beyond the standard calibration pipeline You should read both INTRO 3 and chapter 4 carefully before reducing your data in order to be fully aware of the relevant issues and to obtain the best results from your observations 3 1 Pipeline Processing OTFR and the HST Archive During Cycle 7 and 7N NICMOS data arriving at STScI followed the standard path for processing and archiving They passed through the OPUS pipeline which processed and calibrated them and the resulting raw and processed data products were recorded as static entities in the HST NICMOS 3 1 NICMOS 3 2 J Chapter 3 Calibration Data Archive Users interested in reprocessing their NICMOS observations could retrieve the raw data and reference files from the archive and process them at their home institutions using STSDAS software If you have received NICMOS data as a GO or from the HST Archive before late September 2001 your data was processed in this fashion Beginning 26 September 2001 NICMOS data are now retrieved from the HST Archive using On The Fly Reprocessing OTFR a method previously implemented for STIS and WFPC2 and which will be used for all data from future HST instruments as w
246. ience instrument apertures of HST 1 Will process all groups of a multigroup GEIS file 3 3 3 Working with STIS ACS and NICMOS Imsets STIS ACS and NICMOS data files contain groups of images called imsets associated with each individual exposure A STIS or ACS imset comprises SCI ERR and DQ images which hold science error and data quality information A NICMOS imset in addition to its SCI ERR and DQ images also contains TIME and SAMP images recording the integration time and number of samples corresponding to each pixel of the SCI image See the STIS ACS and NICMOS Data Structures chapters for more details on imsets Analyzing HST Images W INTRO 3 15 Here we describe several STSDAS tasks located in the stsdas toolbox imgtools mstools package that have been designed to work with imsets as units and to deconstruct and rebuild them msarith This tool is an extension of the IRAF task imarith to include error and data quality propagation The msarith task supports the four basic arithmetic operations and can operate on individual or multiple imsets The input operands can be either files or numerical constants the latter can appear with an associated error which will propagate into the error array s of the output file Table 3 4 below shows how this task operates on the SCI ERR and DQ images in a STIS ACS or NICMOS imset as well as the additional TIME and SAMP images belonging to NICMOS imsets Table
247. iformity as well as pixel to pixel fluctuations figure 4 6 The flat field variations are also a strong function of the wavelength At 0 8 um there is variation by a factor of 5 minimum to maximum in the relative response across the array This declines to a factor of 3 at a wavelength of 2 2 um and at 2 5 um the array is almost flat Naturally both the spatial distribution and amplitudes of these variations are different for each camera Camera 3 has an overall side to side response gradient making one half of the array generally more efficient than the other Camera 1 has a large contiguous region with low sensitivity An inevitable consequence of these large QE variations is that science data will have large spatial variations in their pixel to pixel noise level and hence in signal to noise for sources For images where statistics are limited by photon shot noise either from the sources themselves or from the sky background the S N variations scale as the square root of the flat field amplitude e g a factor of 2 at FI60W Many NICMOS observations however especially with Cameras 1 and 2 are largely readout noise limited and for these the signal to noise modulation will scale linearly with the flat field e g a factor of 4 at F160W Flatfielding Hi NICMOS 4 25 Figure 4 6 NICMOS flatfields From left to right NIC1 F190N NIC2 F237M and NIC3 F222M Lighter shading indicates regions of lower sensitivity The corona graphi
248. in NICMOS the reduction techniques described below permit accurate polarimetry using both cameras over their full fields of view A complete set of polarimetric observations will contain images obtained in all three polarizers of the selected wavelength range We assume that each image has been processed through calnica and calnicb to produce a fully reduced and if necessary mosaiced image in each of the three filters with the data corrected for saturation and cosmic rays and converted to flux density using the appropriate photometric calibration constants for the polarizers To generate Stokes parameters the relative differences in flux between images in the different polarizing filters are used Where the signal level is very faint and the signal to noise ratio is very low the differences may be very large but dominated by noise If you attempt to calculate the Stokes parameters using such data you will likely obtain large and entirely spurious polarizations Therefore it is not advisable to use low signal to noise data to calculate polarization To avoid this problem it is suggested to estimate the noise in an area of the image free of sources and then set a threshold at a value of order five to ten times this noise level Using the IRAF task imreplace all pixels with signals below this threshold should be set to some arbitrary value probably close to the measured noise level This action will cause all areas of the image where the signa
249. in principle any image may be used to represent the spatial structure of the sky i e you do not need to use a standard NICMOS flatfield reference file In particular for some NICMOS images the two dimensional structure of the sky may not exactly resemble that of the flatfield This may happen for at least two reasons First as will be discussed below section 4 4 2 the NICMOS flatfields are strongly color dependent and the spectrum of the internal flatfield lamps does not necessarily match that of the sky background especially at longer wavelengths gt 1 8 um where thermal emission begins to dominate over the zodiacal sky The result is that the spatial structure of the sky may not be quite the same as that of the flatfield and that the sky multiplied by the inverse flat reference file may have some residual structure which correlates with the flatfield pattern and contributes to the total image variance X measured by pedsky This can confuse pedsky resulting in improper sky and pedestal measurement This problem is most important for images dominated by thermal background but may also affect shorter wavelength data especially for Camera 3 data where the ratio of background counts to quadrant bias offset amplitude is larger than for the other two cameras Second at longer wavelengths the thermal background generated within the telescope may illuminate the detector differently than does the zodiacal sky and thus the overall background m
250. in the hst_calib ctools package See online help for details The STSDAS task sgraph in the graphics stplot package can plot the contents of a single GEIS group For example if you want to see group 19 of the calibrated FOS spectrum with rootname y3b10104t you can type st gt sgraph y3b10104t clh 19 Given an input flux image clh the task fwplot in the hst_calib ctools package will look for the corresponding wavelength cOh file and plot flux versus wavelength If requested it will also look 3 4 2 Displaying HST Spectra J INTRO 3 21 for the error c2h file and plot the error bars To see a plot of the same spectrum as above but with a wavelength scale and error bars type st gt fwplot y3b10104t clh 19 plterr If you ever need to plot the contents of multiple groups offset from one another on the same graph you can use the grspec task in the graphics stplot package For example to plot groups 1 10 and 19 of a given flux file you can type st gt grspec y3b10104t clh 1 10 19 Note that grspec expects group numbers to be listed as a separate parameter rather than enclosed in the standard square brackets STIS Spectra STIS data files retrieved from the Archive can contain spectra in two different forms as long slit spectral images in FITS IMAGE extensions or as extracted echelle spectra in FITS BINTABLE extensions You can use sgraph to plot STIS long slit spectra by specify
251. in the current directory with initial values from the first image using the command ct gt chcalpar n raw fits 2 After starting chealpar you will be placed in eparam the IRAF parameter editor and will be able to edit the set of calibration key words Change the values of any calibration switches reference files or tables to the values you wish to use for recalibrating your data Exit the editor when you are done making changes by typing q two times The task will ask if you wish to accept the current settings If you 66 99 type y the settings will be saved and you will return to the IRAF cl 6699 prompt If you type n you will be placed back in the parameter editor to 66 99 redefine the settings If you type a the task will abort and any changes will be discarded As delivered from the archive image header parameters which specify the names of the calibration reference files e g FLATFILE DARK FILE etc take the form nref name_extfits or ntabSname_ext fits The prefixes nref and ntab are environment variables pointing to the CDBS directories where the reference files reside at STScI This can be convenient and you may wish to keep your calibration reference files in a particular directory when reprocessing your data However because calnica is a stand alone C program called by IRAF the envi ronment variables nref and ntab must be defined at the system host level before s
252. in unpredictable ways see e g the discussions of data anomalies such as cosmic ray persistence in chap ter 4 DARKCORR Dark Current and Bias Shading Subtraction Dark images taken with NICMOS contain three distinct additive signal components the so called shading amplifier glow and the true dark current The shading is a noiseless signal that appears as gradient across a detector quadrant and is due to the fact that the bias level on the pixels is gradually changing as they are being read out The amplitude of the shading signal is a function of the time since a pixel was last read out The amplifier glow is signal produced by a small amount of infrared radiation from the detector readout amplifiers The amplitude of the amplifier glow is directly proportional to the total number of readouts in an observation The true detector dark current signal is quite small for the NICMOS arrays and is linearly dependent on the total exposure time of an observation Because the shading and amp glow signals depend on factors other than the exposure time of an observation it is not possible to apply a simple scaling of a single dark reference image to match the exposure time of the science data that is being calibrated Therefore a library of dark current images is maintained for each of the three cameras covering all of the predefined MULTIACCUM sample sequences and a subset of ACCUM exposure times and NREAD values see the NICMOS Instrume
253. ing NICMOS when to NICMOS 3 23 software STSDAS INTRO 3 1 switches NICMOS NICMOS 3 25 NICMOS 1 NICMOS 2 Index calnica task algorithm NICMOS 3 5 NICMOS calibration NICMOS 3 3 calnicb task mosaiced NICMOS image NICMOS 3 16 NICMOS calibration NICMOS 3 3 calnicc task NICMOS grism spectroscopy calibration NICMOS 3 4 chcalpar task NICMOS calibration switches NICMOS 3 25 chop pattern NICMOS background NICMOS 3 21 command see task commands splot cursor INTRO 3 33 conversion counts to flux or magnitude INTRO 3 18 NICMOS 5 6 flux to wavelength resample task INTRO 3 24 cosmic ray identification NICMOS NICMOS 3 15 counts flux conversion INTRO 3 18 magnitude conversion INTRO 3 18 cursor splot commands INTRO 3 33 D dark subtraction NICMOS NICMOS 3 11 data analysis software STSDAS INTRO 3 1 parameter types IRAF APP A 10 data quality PDQ files APP B 4 database synphot APP A 16 dataset NICMOS NICMOS 2 2 see also imset differential photometry NICMOS NICMOS 5 13 digiphot package PSF subtraction NICMOS 5 23 disconlab task position display INTRO 3 10 display display task INTRO 3 4 image INTRO 3 4 SAOimage INTRO 3 6 spectra INTRO 3 20 display task images in STSDAS INTRO 3 5 dither pattern NICMOS background NICMOS 3 21 documentation IRAF INTRO 3 37 STSDAS INTRO 3 37 E echelle spectra echplot task INTRO 3 22 echplo
254. ing the image section that contains the spectrum For example to plot the entire x range of the calibrated two dimensional spectrum in the first extension of the file o43balbnm_x2d fits averaging rows 100 through 1000 you would type st gt sgraph o43balbnm_x2d fits 1 100 1000 Displaying the long slit spectral image using the display task see section 3 2 1 in the HST Introduction allows you to see the range of your spectrum in x and y pixel space so you can choose a suitable image section for plotting To plot STIS spectra in BINTABLE extensions you first need to understand how STIS spectra are stored as binary arrays in FITS table cells Chapter 2 section 2 2 2 discusses this format and describes the selectors syntax used to specify these data arrays Each row of a STIS echelle table contains a separate spectral order and each column contains data of a certain type such as WAVELENGTH data or FLUX data To specify a particular array you must first type the file name then the extension containing the BINTABLE then the column selector then the row selector For example to select the WAVELENGTH array INTRO 3 22 Chapter 3 STSDAS Basics 3 4 3 corresponding to spectral order 80 of the echelle spectrum in extension 4 of stis fits you would specify the file as stis fits 4 c WAVELENGTH r sporder 80 The sgraph task and the igi plotting package to be discussed below both understand the selectors syntax
255. ing through the hole from warmer structures behind it The position of the hole in detector coordinates drifted with time during the lifetime of the instrument changing rapidly shortly after launch when the cryogen distortion of the dewar was varying quickly then slowly stabilizing Cures The hole should usually be treated as bad pixels when combining dithered NIC2 images either by masking or interpolation Masking a 4 5 4 Pixel Defects and Bad Imaging Regions IJ NICMOS 4 29 circular region with radius 7 pixels should eliminate the effects of the hole for most data sets Tables and graphics showing the location of the coronagraphic hole as a function of time are available on the STScI NICMOS Instrument WWW page at http hst stsci edu nicmos performance coronagraphy You may also retrieve information about the coronagraphic hole position for a given dataset using the NICMOS History Tool see section 5 2 For coronagraphic imaging science see the discussion on reducing coronagraphic data in chapter 5 Vignetting There are two effects which are sometimes described as vignetting in the NICMOS cameras First the anomalous expansion of the NICMOS dewar moved the cameras in such a way that they image the edge of the Field Divider Assembly FDA at the bottom of all 3 cameras The FDA is a fold mirror that sends the light from the foreoptics down each camera channel and through the filters and dewar window to the cameras Th
256. ion ZSIGCORR Zero Read Signal Correction At the beginning of a NICMOS observation the detector pixels are reset to a bias level and then read out to record that bias level There is an interval of approximately 0 2 seconds that elapses between the time each pixel is reset and then read Because NICMOS does not have a shutter signal from external sources starts to accumulate during that 0 2 second interval When the initial or zeroth read is later subtracted from subsequent readouts any signal in the zeroth read will also be subtracted For very bright sources the amount of signal in the zeroth read can be large enough to lead to inaccurate linearity corrections as well as the failure to detect saturation conditions in the NLINCORR calibration step because the linearity correction and saturation checking both depend on the absolute signal level accumulated in a pixel For MULTIACCUM observations the ZSIGCORR step is used to estimate the amount of source signal in the zeroth read and to supply corrections to the NLINCORR step for that signal The ZSIGCORR step estimates the amount of signal in the zeroth read by first measuring the amount of signal that arrived in each pixel between the zeroth and first reads and then scaling that signal to the effective exposure time of the zeroth read nominally 0 203 seconds Pixels that have an estimated zeroth read signal greater than 5 times their ERR value are assumed to contain detectable si
257. ion product lists the exposures belonging to the association You can read this file using the STSDAS tprint or tread tasks see table 3 1 in the HST Introduction The exposure IDs in the association table share the same ipppss sequence as the association rootname followed by a base 36 number nn n 0 9 A Z that uniquely identifies each exposure and a character t that denotes the data transmission mode see figure B 1 In practice STIS and NICMOS store the exposures belonging to associations differently The exposures belonging to a STIS association all reside in the same file while the exposures belonging to a NICMOS association reside in separate datasets See the relevant Data Structures chapters for more details Information on the exposures belonging to an association is also available through StarView see chapter 1 of the HST Introduction From the lt Welcome gt Screen click on HST Instrument Searches to get the lt HST Instruments gt screen and then click on the Associations button for the instrument of interest You can then search for the various exposures belonging to an association by entering the rootname of the association in the Association ID field and clicking on Begin Search An Association Results Screen will display the results of the search which you can step though using the Step Forward button Figure B 1 below gives an example of a NICMOS Association Results Screen Note the differences between the assoc
258. ion of the coronagraphic hole measured from the pipeline processed image is 73 384 213 082 while the measured position of the hole from the off line processed image is 73 273 213 163 The difference is 0 1 pixel in the x and y positions This measured offset in hole position is most probably due to the different calibrations performed on the ACQ images The pipeline processed ACCUM images are not dark or background corrected The location of the coronagraphic hole in the pipeline on orbit flat was patched and could contribute to error in determining the position of the hole 5 6 4 Coronagraphic Reductions J NICMOS 5 35 For comparison with the FSW determined position of the hole the IRAF positions of the hole need to be converted into detector coordinates by subtracting them from 256 5 For example Hole NYHOLE 256 5 73 273 183 227 NXHOLE 256 5 213 163 43 337 In this example for back to back orbit ACQ images n4q832npq and n4q833nzq obtained prior to June 28 1998 the difference between the two positions derived for the hole RAF and FSW in detector coordinates is 0 9 pixels in y and 0 3 pixels in x This is much larger than can be explained by summing the errors of the target and hole positions in quadrature and is due to a bug in the early version of the FSW which introduced errors in the derived hole positions Measuring the Target Position The IRAF task center can be used to determine the cent
259. ion time of the sample sec UT time of array readout MJD Keywords in the support file _spt fits report information from the ephemeris and engineering data on the status of the telescope and of the instrument during the observations Information common to all readouts of a MULTIACCUM sequence are stored in the primary header of the support file while information which may change from readout to readout e g detector temperature is stored in the headers for each corresponding NICMOS 2 16 E Chapter 2 Data Structures extension Table 2 5 describes some of the relevant primary header keywords from the _spt fits file and table 2 6 gives some useful keywords from the extension headers Table 2 5 NICMOS Primary Header Keywords in the Support Files Keyword Name Meaning PA_V3 Position angle of the V3 axis of HST degrees PA_V3 RA of the V1 axis of HST degrees in J2000 RA_VI1 DEC of the V1 axis of HST degrees in J2000 DEC_V1 RA of the Sun degrees in J2000 RA_SUN DEC of the Sun degrees in J2000 DEC_SUN RA of the Moon degrees in J2000 RA_MOON DEC of the Moon degrees in J2000 Table 2 6 Some Useful NICMOS Extension Header Keywords in the Support Files Keyword Name Meaning NDWTMPI11 Camera 1 and 2 Mounting Cup temp deg K NDWTMP13 Camera 3 Mounting Cup temp deg K 2 3 Working with NICMOS Files The quickest way to learn how each observation was performed is to use the iminfo task in
260. ions amount to lt 2 rms Much larger variations are seen for Camera 3 but are due to a different effect intrapixel sensitivity variations which we will discuss next Intrapixel Sensitivity Variations and Camera 3 As with many other infrared arrays NICMOS detector sensitivity varies across the area of each physical pixel It is higher in the center and lower near the edges In practical terms this means that for a source whose flux changes rapidly on a scale comparable with or smaller than that of a pixel the measured countrate and therefore the derived flux will depend on where the center of the source lies with respect to the center of the pixel For NICMOS cameras 1 and 2 the PSF is sufficiently well sampled that intrapixel sensitivity variations do not introduce a large or at least not a dominant effect on point source photometry Camera 3 images however are highly undersampled and the exact position of a point source relative to the pixel grid can introduce large variations in the measured signal Measurements made using calibration test data as well as science data with large numbers of dither positions show that the flux variation can be as large as 30 The tighter the PSF is the larger these variations will be For that reason in focus images taken during the two Cycle 7N refocus campaigns are more subject to the impact of intrapixel sensitivity variations although the effect is still appreciable for non campaign
261. ired One could for example process a science data file through some subset of the normal calibration steps performed by calnica examine or modify the results and then process the data through calnica again performing other calibration steps or using alternate calibration reference files One example of such a procedure would be reducing data where there are significant changes in the quadrant bias level from readout to readout in a MULTIACCUM sequence In section 4 1 we discuss this common NICMOS data anomaly and in section 4 1 5 we describe one technique for treating it using the biaseq task At present the use of this routine requires multiple re entrant applications of calnica in order to partially process the images before and after the use of the biaseq task Figure 3 1 shows the portion of a calibrated NICMOS science file header containing the switches and reference file keywords that pertain to the processing performed by calnica The accompanying flow chart figure 3 2 shows the sequence of calnica calibration steps the input data and reference files and tables and the output data file Each calibration step is described in detail in the following sections NICMOS 3 6 Chapter 3 Calibration Figure 3 1 Partial NICMOS Header cal cl CALNICA CALIBRATION REFERENCE FILES MASKFILE nref h4214599n_msk fits static data quality file NOISFILE nref h4216218n_noi fits detector read noise file NLINFILE
262. is site also includes a FAQ page and news on releases and updates StarView will automatically update itself to the latest version so users do not have to worry about additional installations Following its installation on computers running Unix and Linux begin StarView by typing gt StarView at the system prompt Under Windows and MacIntosh systems StarView will appear as an icon The StarView session then begins first with an Information window explaining navigation within StarView and a request for the user to specify an object name resolver SIMBAD or NED for use in HDA searches The first time user are asked to supply their e mail information in order to allow StarView to communicate the results of its attempts to retrieve the files requested from the HDA This e mail information includes the user s SMTP host or the computer from which e mail messages are routed If unsure of your SMTP host ask your system administrator These queries can be turned off for future sessions once this information has been supplied Simple Use of StarView We now proceed to an introduction to the use of StarView A more detailed description of its capabilities is provided at the web site above which should also be consulted for more advanced topics such as its Table Exportation and Cross Qualification functions The basic function of StarView is to enable the user to first search the HDA and the other mission archives in MAST for data files matc
263. is to stack the images of different groups together as a new dimension in the FITS image As for group parameters they are put in an ASCII table and the table becomes the first and only extension of the FITS file For example the WFPC2 pipeline generates the science data as a GEIS file of 4 groups each is an 800x800 image corresponding to one of the 4 INTRO 2 18 Chapter 2 HST File Formats detectors When this GEIS file is converted to the waiver FITS file the FITS file has an image of 800x800x4 a three dimensional image at its primary HDU Similarly an FOS GEIS file may have 40 groups each group is a 1 D image spectrum of the size 2064 The waiver FITS file then will have one 2 D image of the size 2064x40 at its primary HDU In the case of WFPC2 the first extension of the waiver FITS file will be an ASCII table containing 4 rows each row corresponds to a group The value of each group parameter is under a column named after the group parameter i e the value of the group parameter CRVALI of the 2nd group will be at the 2nd row under the column named CRVAL1 In other words the ASCII table has as many rows as there are groups in the original GEIS file and as many columns as group parameters Although in theory certain IRAF STSDAS tasks can directly access the data in the waiver FITS file e g to display the 2nd group of a WFPC2 image st gt display u67m0206r cOf fits 0 2 will work while
264. ith CCDs Exposure to bright sources however can result in two other sorts of NICMOS artifacts persistent images and electronic ghosts known colloquially as the Mr Staypuft anomaly Photon Persistence HgCdTe detector arrays are subject to image persistence When pixels collect a large amount of charge they will tend to glow for some time after the end of the exposure This persistent signal decays exponentially with a time scale of about 160 60 seconds but there is also a long roughly linear tail to the decay such that persistence from very bright sources remains detectable as much as 30 to 40 minutes after the initial exposure Exposures of bright astronomical targets therefore can leave afterimages which appear in subsequent exposures taken within the same orbit or even into the next figure 4 7 If you are analyzing dithered exposures of a bright target you may wish to carefully inspect each image for residual ghosts from the previous exposure s and perhaps mask them 4 6 2 Effects of Overexposure J NICMOS 4 31 out when coadding the dithered images It appears that all sources of illumination probably leave persistent afterimages but under typical conditions they are most noticeable for sources which have collected 20 000 or more ADU during the previous exposure It is not unreasonable to expect afterimage signals of 1 e second immediately following a severe over exposure Occasionally persistent images result from bri
265. ks The NICMOS dark calibration reference files which are used in the HST Archive pipeline processing are so called synthetic dark images These include the linear dark current amplifier glow and bias shading terms described above The synthetic darks were constructed using on orbit measurements of the linear dark current and amplifier glow plus an empirical shading model based on a fit to on orbit data Random Uncertainties i e noise in the Synthetic Darks In the center of the NICMOS arrays where the effects of shading and amplifier glow are smallest the uncertainties in the dark reference files are dominated by the readout noise The older STScI synthetic darks were typically based on an average of about 15 measurements per readout sample per pixel Therefore the estimated pixel to pixel uncertainties in the DARK reference files are of the order of 1 DN about 5 electrons In the x N KN 2 NICMOS Dark Current and Bias IJ NICMOS 4 11 comers of the arrays the amplifier glow is the largest source of noise increasing as a function of the number of readouts For the largest number of readouts 26 the estimated uncertainty is of the order of 5 DN about 27 electrons It is important to note that the effect of these random uncertainties in the calibration files on science data is not actually random however The pixel to pixel noise pattern in the DARK reference files is systematically imprinted on all science images from
266. ks They can be the names of input or output files particular pixel numbers keyword settings or many other types of information that control the behavior of the task The two most useful commands for handling parameters are e Iparam to display the current parameter settings often abbreviated Ipar e eparam to edit parameters often abbreviated epar Viewing Parameters with Iparam The Ipar command lists the current parameter settings for a given task figure A 5 Figure A 5 Displaying Parameter Settings with Ipar Type lpar STSDAS Followed by gt ft i gt Ipar strtits Name of Task fits_file mtg FITS data source file_list 1 999 File list iraf_file IRAF filename template template filename Parameters and long_header no Print FITS header cards i short_header yes Print short header Current Settings Cites default IRAF data type blank s Blank value scale xdimtogf Coldirafname yes Use old IRAF name in place of iraf_file offset 0 Tape file offset mode ql yes Scale the data yes Transform xdim FITS to multigroup Setting parameters with eparam The epar command is an interactive parameter set editor It displays all of the parameters and their current settings on the screen You can move around the screen using the arrow keys also called cursor keys and type APP A 10 J Appendix A IRAF Basics new settings for any parameters you wish
267. l first coordinate type second coordinate type partial of ra w r t x deg pixel partial of ra w r t y deg pixel partial of dec w r t x deg pixel partial of dec w r t y deg pixel image coordinate system plate scale along x mas plate scale along y mas parity between V2V3 frame and image frame per pixel per pixel angle from V3 to image x toward V2 angle from V3 to image y toward V2 OBSERVATION DATA PEP proposal identifier program id base 36 observation set id observation number base proposer s target name predicted observation window start time 36 predicted observation window end time SOGS observation name SCIENTIFIC INSTRUMENT DATA proposed instrument configuration single parallel primary parallel secondary predicted time instr entered operate mode telemetry format aperture name v2 aperture position in vehicle frame arcsec V3 aperture position in vehicle frame arcsec SPACECRAFT DATA average altitude during observation minimum line of sight to minimum line of sight to predicted Earth shadow predicted Earth shadow minimum line of sight to average line of sight to BACKGROUND LIGHT Sun deg Moon deg last entry last exit S C veloc Earth limb km deg deg zodiacal light model V mag arcsec2 peak Earth stray light model V mag arcsec2 moon stray light model V mag arcsec2 diffuse galactic light model V mag arcsec2
268. l highlighting their stability or lack thereof and describing briefly how they are incorporated into the standard STScI synthetic dark reference images In section 4 1 5 below we describe methods and tools for measuring and removing residual dark and bias artifacts from NICMOS images Dark Current Linear Dark Current The true thermal dark current is the detector current when no external signal is present This component grows linearly with integration time D x y t dc x y x t where D x y t is the observed signal in a given readout is time since reset and dc x y is the dark current At the operating temperatures used for NICMOS in Cycle 7 the mean dark current for all three cameras was of order 0 1 e sec It is likely to be higher in Cycle 11 when operating at warmer temperatures with the NCS The dark current has some two dimensional structure and is roughly a factor of two higher in the corners than at the center Amplifier Glow Each quadrant of a NICMOS detector has its own readout amplifier which is situated close to an exterior corner of the detector When a readout is made the amplifier emits radiation which is recorded by the detector an effect known as amplifier glow figure 4 1 This signal is largest close to the corners of the detector where the amplifiers are situated and falls off rapidly towards the center of the array The signal is only present during a readout but is repeated for each readout e g a
269. l level is very faint to show zero polarization To further increase signal to noise bin the data in each of the three images before computing the Stokes parameters Once the parameters have been derived clipping the Q and U images at 1 and the polarization intensity image at values lt 0 or gt 1 will also help in increasing the signal to noise Analysis of Polarized Light with NICMOS by Hines Schmidt amp Schneider 2000 PASP 112 983 is a highly valuable reference dis cussing NICMOS polarimetric measurments and data analysis NICMOS 5 44 Chapter 5 Data Analysis 5 7 2 Theory In order to reduce data obtained with a set of polarizers three quantities are needed They are the throughput for unpolarized light the efficiency of the element as a polarizer and the orientation of the polarizer These quantities can be expressed in a polarization reduction algorithm to form a solution containing the polarization characteristics of the incoming beam i e the Stokes parameters J Q and U The general form of the equation for polarimetric data reduction is expressed as I Al 4 B O C U where T 18 the emerging light intensity from the Ath polarizer A By and C are the transmission coefficients and is the polarizing efficiency This linear equation captures the observed signal from a polarized source of intensity 7 and linear Stokes parameters Q and U which describe the state of polarization for the ta
270. l3jwq_clf fits OMIT ver PERFORM ver OMIT ver OMIT ver PERFORM ver OMIT ver gt n4xj1l3jwq_btrl log gt n4xjl3jwq_ftrl log mscombine n4xj13jwq_clb01 fits n4xj13jwq_clb02 fits n4xj13_bck mscombine n4xj13jwq_clf01 fits n4xj13jwq_clf02 fits n4xj13_lamp msarith n4xj13_lamp fits n4xj13_bck fits n4xj13_lamp_bck msstat n4xj13_ lamp bck fits sci 1 1 256 36 256 msarith n4xj13_lamp_bek fits 1169 64 norm_lamp_bck msarith 1 0 norm lamp bck n4xj13_f160w_flt hedit n4xj13_f160w_flt fits 0 PEDIGREE Contemporary 31 08 98 add NICMOS 5 38 Chapter 5 Data Analysis 5 6 5 Recalibrating the ACQ ACCUM Images Some observers have expressed the desire to obtain photometry from the ACQ images of their targets These images are not dark corrected and will need to be recalibrated As discussed in section 4 1 3 however at the present time there are no standard dark reference files for ACCUM mode images Appropriate DARK exposures matching the ACQ image exposure times may be available in the HST Archive If you are a NICMOS GO please speak with your contact scientist CS about dark subtraction for ACCUM images or contact help stsci edu We note here that due to a software bug the exposure time stated in the header keyword EXPTIME is in error for ACQ data taken prior to October 19 1998 The commanded exposure time listed in the SHP and UDL data file _ spt fits should be used for photometry For e
271. lable 5 8 2 Grism Data Reduction IJ NICMOS 5 49 Calibration data and configuration files for the extraction programs are in directory calib The ASCII file grismspec dat describes grism parameters and calnicc setup specifies configuration parameters Parameters interactively changed and saved with NICMOSlook are written to those files File names of other calibration data are specified in those two files Output Files The basic output of the extraction are the spectra which can be saved in several forms 1 A FITS table containing the extracted spectra image_spc fits This file contains the successfully extracted spectra it consists of a primary header and a series of table extensions each extension con sisting of a header and the associated table There is one table exten sion for each spectrum extracted The primary header of the file contains the relevant information regarding the observation namely a subset of the keywords in the primary headers of the input direct and grism images The table extension header contains keywords relevant for the individual spectrum the keywords describe the content of the table the list of columns the nature and position of the object and the characteristics of the spectrum line positions and fluxes contin uum level etc The associated table contains five columns the wavelength vector the flux vector and three vectors of the statistical deblending and total errors from the extra
272. lats can be significantly different from flats through regular filters and do a better job of removing the background once they are inverted and scaled to match the background in the spectral image Extraction of Spectra Flux and Error Bars Once objects on the images have been detected their spectra can be extracted The flux is then given by F D WZ L where the sum over the flux gj of all pixels at wavelength A is performed with weights w N Grism Data Reduction HJ NICMOS 5 51 Several options for the weights can be used to achieve optimum S N Constant weights lead to an optimum extraction for high S N spectra while for background limited objects weights can be derived from the profile of the spectrum to be extracted The profile can either be determined directly from the spectrum or predicted from the direct image for very low S N spectra under the assumption that the shape of the object is independent of wavelength First the size and orientation of the object is computed from the direct image using the moments of the image The weights are then created by summing up all the pixel values in a given column fixed wavelength of the grism image that fall within the ellipse defined by the size and orientation of the object in the direct image Since NICMOS grism images are undersampled spectra of point sources and sources up to the size of a few pixels are best extracted using constant weights even for low SIN spectr
273. leasant consequences this tends to trigger the CRIDCALC cosmic ray detection flags causing wholesale rejection of many or most time steps for the affected pixel Images which have been affected by this problem will generally have anomalously low count rates for bright pixels but the saturation flag 64 will not be set in the DQ arrays Cures The simplest cure is to modify the nonlinearity reference file to reduce the threshold where saturation flagging is triggered and then to reprocess the data The saturation level for each pixel is set in the NODE 2 extension of the nonlinearity reference file As an example let us say that the science image is called n4ux22hbq raw fits and the corresponding nonlinearity reference file ish7n1654cn_ lin fits We reduce the saturation threshold by 5 edit the science image primary header to point to the new reference file and reprocess NICMOS 4 24 Chapter 4 Anomalies and Error Sources ni gt copy h7n1654cn_lin fits new_nonlin fits ni gt imarith new_nonlin fits NODE 2 0 95 gt gt gt new_nonlin fits NODE 2 overwritet ni gt hedit n4ux22hbq raw fits 0 NLINFILE new_nonlin fits gt gt gt update verify show ni gt calnica n4ux22hbq If the problem reoccurs reduce the NODE 2 values further until the saturation threshold is properly triggered 4 4 Flatfielding 4 4 1 Characteristics of NICMOS Flatfields NICMOS flatfields show significant large scale non un
274. led on your system to install TABLES and w STSDAS When you retrieve STSDAS you must also retrieve the TABLES package and TABLES must be installed first Instructions for installing STSDAS are available in the doc subdirectory of the directory where you find STSDAS The complete instructions for installing STSDAS TABLES and all of the supporting software and reference files including instrument reference files and the synphot dataset are found in the STSDAS Site Manager s Installation Guide and Reference Registration The software can also be registered and requested using on line forms available through World Wide Web at the following URL http stsdas stsci edu RegistForm html When you request the STSDAS software you can also ask for the appropriate version of IRAF which will be requested for you simply check the appropriate box on the form under Do You Already Have IRAF Installed If you prefer to request the IRAF software independent of STSDAS you can do so by sending e mail to iraf iraf noao edu A 3 2 Getting the Synphot Database This manual sometimes refers to the synphot dataset which must be available in order to run tasks in the STSDAS synphot package These data files are not included with the STSDAS software and must be retrieved independently To do this you need to retrieve a series of compressed tar files from the STScI FTP site ftp stsci edu in the directory software stsdas refdata synphot Afte
275. les for all cameras have been generated at STScI which implement a temperature dependent shading correction These new files also average a larger number of individual frames for the lin ear dark current measurements providing better signal to noise for the DARK reference files The new darks are not yet used in standard Archive OTFR but can be obtained using the new WWW based tem perature dependent synthetic dark generation tool see section 4 1 5 below Users must then reprocess the data locally using these darks Initial tests show that using these new darks can significantly reduce pixel to pixel noise in processed data and improve the shading correc tion NICMOS 4 12 Chapter 4 Anomalies and Error Sources On Orbit Darks All dark images taken with NICMOS are available through the HST Archive Certain MULTIACCUM sequences have extensive collections of on orbit dark data particularly those used for the dark monitoring program Other NICMOS MULTIACCUM sequences however have very little on orbit data Users wishing to use on orbit dark data instead of synthetic darks may retrieve darks for the camera of interest with the appropriate MULTIACCUM sequence and the correct number of readouts NSAMP process them by subtracting the zeroth readout ZOFFCORR and combine them on a readout by readout basis with some suitable rejection scheme to eliminate cosmic rays e g median or sigma clipping In practice there are several difficulties
276. ll as a history of its performance throughout its lifetime The proceedings to the 1997 HST Calibration 1 Thompson R I M Rieke G Schneider D C Hines and M R Corbin 1998 ApJL 492 L95 NICMOS 1 1 NICMOS 1 2 Chapter 1 Instrument Overview Workshop eds S Casertano R Jedrzejewski T Keyes amp M Stevens STScI publication also include useful information about NICMOS and its calibration and performance although some of that information is now superseded by material included in this handbook and other more recent documents Finally the NICMOS edition of the Space Telescope Analysis Newsletter STAN which is periodically distributed by e mail provides regular notices and updates to information about NICMOS and NICMOS data reduction Back issues of the NICMOS STAN are archived at the STScI NICMOS web site The first phase of life for NICMOS took place during HST Cycle 7 with a special supplemental call for proposals issued as Cycle 7N Its cryogens were exhausted in January 1999 and the instrument was deactivated and subsequently decommissioned In HST Cycle 11 the installation of the NICMOS Cooling System NCS is expected to bring NICMOS back down to cryogenic temperatures and thus return it to regular service Its performance with the NCS is naturally unknown at this time although predictions are presented in the most recent edition of the NICMOS Instrument Handbook This edition of the NICMOS Dat
277. ll not always be effectively removed by the calnica CRIDCALC processing The core of the very bright CR will be flagged and removed but there can be a large surrounding halo of pixels weakly affected by CR signal that are not flagged Also glancing incidence cosmic rays can leave long trails across an image and the weaker CR pixels in the streak may not be flagged by the CRIDCALC processing Very strong CRs can induce persistence which will alter the count rate for the rest of the MULTIACCUM sequence resulting in a cosmic ray afterimage If pixels reach saturation levels from a cosmic ray impact subsequent readouts are unrecoverable NICMOS 4 38 J Chapter 4 Anomalies and Error Sources N Figure 4 11 A monster cosmic ray hit in a NICMOS image The brightest pixels of the CR have been cleaned by CRIDCALC in calnica but a surrounding halo of affected pixels remains as does a long diagonal streak of unflagged pixels from the CR s glancing traversal of the array Also note the vertical Mr Staypuft streaks see section 4 6 3 in both the left and right halves of the image which are evidently induced by the CR impact itself Unremoved glancing CR Monster CR 3 l Cures If weakly affected pixels around bright cosmic rays are not being flagged by CRIDCALC you may wish to reprocess the data reducing calnica s CR rejection threshold parameter crthresh from the default 4 to a smaller value Alternatively you may fl
278. ly nonlinearity calibrations used for all Cycle 7 and 7N data processed retrieved from the HST Archive before 26 September 2001 used a low order correction which worked well for most purposes However the STScI NICMOS group has subsequently recalibrated the detector nonlinearities and produced improved NLINFILE reference files There are two significant changes e In the old nonlinearity calibrations data values below a minimum threshold set for each pixel by the value in the NODE 1 extension of the nonlinearity reference file had no calibration applied How NICMOS 4 22 Chapter 4 Anomalies and Error Sources 4 3 2 ever NICMOS data are actually nonlinear at all levels and in the new reference files the linearity correction will be calibrated and applied at all count levels e Previously only corrections of the form F c7 c2 F F were allowed The new reference files and software will permit 2nd order corrections terms which improve the accuracy of the linearity calibra tion see section 3 3 The new nonlinearity reference files are now used by default when data are retrieved from the archive and processed by OTFR Version 3 3 of calnica accommodates second order correction scheme used in the new reference files Non Zero zeroth Read Correction for Bright Sources As described in section 4 1 2 above the first non destructive readout after a reset provides the reference bias level for the counts in each pixel of
279. m the HST Archive via OTFR which will automatically apply the ZSIGCORR step ZOFFCORR Subtract Zero Read Image The ZOFFCORKR step of calnica performs the subtraction of the zeroth read from all readouts in a MULTIACCUM file This step is performed for data generated by the MULTIACCUM readout mode only For ACCUM and BRIGHTOBJ readout modes the subtraction of the zeroth read is performed on board because the images returned to the ground are formed by taking the difference of initial and final non destructive detector readouts The pipeline will subtract the zeroth read image from all readouts including the zeroth read itself Furthermore the self subtracted zeroth read image will be propagated through the remaining processing steps and included in the output products so that a complete history of error estimates and data quality DQ flags is preserved After this step is performed the science data are in the same form as the raw science data from any other observing mode and are processed the same way throughout the remaining steps of calnica No reference files are used by this step MASKCORR Mask Bad Pixels Flag values from the static bad pixel mask file are added to the DQ image This uses the MASKFILE reference file which contains a flag array for known bad hot or cold pixels There is one MASKFILE for each detector In general only truly defective pixels are included in the MASKFILE reference images available from t
280. made This information is not always available in the image headers or _spt fits files The STScI NICMOS group has recently implemented a WWW based NICMOS History Tool This tool accepts the exposure start time or the dataset name as input and provides options for retrieving information about the plate scale focus coronagraphic hole position prior SAA passages or the spacecraft attitude history The spacecraft attitude history for example can be important for understanding the behavior of coronagraphic data section 5 6 as is the coronagraphic hole position The hole position is also helpful when reducing non coronagraphic NIC2 data as you may wish to mask out the hole when combining dithered data or to know whether it has affected a target in your field e g section 4 5 3 The SAA information can help you to pre screen your data for frames which may be impacted by SAA induced cosmic ray persistence see section 4 6 2 The plate scale history is important for accurate astrometry and position measurements since the scale of NICMOS varied somewhat with time as the dewar distortion changed see section 5 4 NICMOS 5 6 Chapter 5 Data Analysis 5 3 Photometric Calibrations 5 3 1 5 3 2 Atmospheric absorption bands limit the wavelength ranges over which one can usefully observe in the near infrared from ground based telescopes NICMOS however can observe at any wavelength where its detectors are sensitive and hence its filt
281. mages are usually the calibrated outputs of calnica The support files jpppssoot_spt fits containing engineering information so that calnicb can transfer this information to the out put support files 3 4 2 Output Files Calnicb produces three types of output 1 An updated copy of the association table assoc_id_asc fits this copy of the assoc_id_asn fits file contains additional infor mation about the processing that took place The assoc_id_asc fits file contains four additional columns listed in table 3 2 Table 3 2 Additional Columns of the output Association Table Column Name Meaning eee nn een eee eeeneeeeeeesSsS eee EE ee BCKIMAGE MEANBCK XOFFSET YOFFSET Flag indicating whether or not the image was used to compute the background Values of the mean background for the image DN sec X offset in pixels of the image from the reference frame a positive value means a positive offset of the image not of the sources relative to the reference Y offset in pixels of the image from the reference frame a positive value means a positive offset of the image not of the sources relative to the reference Additional information contained in the header of the assoc_id_asc fits table is the MEAN_BKG keyword which gives the constant background signal level subtracted from all images in the association One or more output mosaic images assoc_idn_mos fits the number of output mosaic images depe
282. mages in combination with significant variation of the QE across any given pixel imposes a wave like pattern onto extracted spectra of point sources and small objects Since spectra are not exactly aligned with the rows of the images the exact sub pixel position and orientation of the spectra determines the phase and period of those waves A simple model can be used to correct this effect for Grism Data Reduction HJ NICMOS 5 53 point sources Details are discussed in an article by W Freudling in the May 1999 issue of the ST ECF newsletter Deblending of Overlapping Spectra Since the NICMOS grisms are slitless overlaps among different spectra are likely to happen The strategy of observing the same target at different telescope roll angles helps remove overlap in many instances The extraction software includes an algorithm designed to remove or minimize contamination of one spectrum from another The deblending algorithm is described in detail in the NICMOSlook software manual The basic requirement for the algorithm to work is that at each wavelength different spatial portions of the spectrum to be deblended have different levels of contamination The deblending algorithm relies on the assumption that the shape of the object is the same at all wavelengths The deblending procedure also produces an error estimate which is reported in the output FITS table and indicated in the postscript file containing the spectrum NICMOS 5 54 Chap
283. me ipppssoot is the root name of the dataset to which the file belongs All files belonging to a given dataset share the same rootname e Suffix The three character second part of the name sfx is called the suffix and it indicates the type of data the file contains Format The identifier fits indicates that this file is in FITS for mat For example an FOC data file named x3180101t_ d0Of fits isa FITS file belong to the dataset with rootname x3180101t and its suffix dOf indicates that it contains raw science data APP B 1 APP B 2 I Appendix B Rootnames Vv In order to use IRAF STSDAS tasks to work with data from instruments other than NICMOS and STIS you will want to convert these FITS files into GEIS format See section 2 2 in the HST Introduction for instructions on how to convert FITS files to GEIS files using strfits Like FITS files the names of GEIS files also derive from a file s rootname and suffix and they look like this ipppssoot sfx Generally the suffixes of GEIS files end either in q indicating a binary data file or h indicating an ASCII header file The two GEIS files x3180101t_d0h and x3180101t _d0d_ together contain the same information as the single FITS file x3180101t_d0Of fits The identifier referred to here as a suffix has often been called an extension in the past However the individual pieces of FITS files are also known as extensions see section
284. nation of the extension number is the most basic method of access but it is not necessarily the most helpful Referring to an extension s EXTNAME and EXTVER in the keyword options is often more convenient If a number follows an EXTNAME IRAF interprets the number as an EXTVER For example if extension number 6 holds the science image belonging to the imset with EXTVER 2 as in the catfits listing on the previous page you can specify it in two equivalent ways fitsfile fits 6 fitsfile fits sci 2 Designations giving an EXTNAME without an EXTVER refer to the first extension in the file with the specified value of EXTNAME Thus fitsfile fits sci is the same as fitsfile fits sci 1 FITS File Format W INTRO 2 7 The syntax for designating image sections adheres to the IRAF standard so in the current example the specifications fitsfile fits 6 100 199 100 299 fitsfile fits sci 2 100 199 100 299 both extract a 100 by 200 pixel subsection of the same science image in fitsfile fits Header Keywords and Inheritance STIS ACS and NICMOS data files use an IRAF image kernel convention regarding the relationship of the primary header keywords to image extensions in the same file In particular IRAF allows image extensions to inherit keywords from the primary header under certain circumstances When this inheritance takes place the primary header keywords are practically indistinguishable from the exten
285. ndar annels ji Webllail Rad Peopl Yellow Pag D load Calend G Ch l Data Search Missions Contacts STScl MAST MAST Multimission Archive at Space Telescope About MAST The Multimission Archive at STScI supports a variety of astronomical data archives with the primary focus Cross Mission on scientifically related data sets in the optical ultraviolet and near infrared parts of the spectrum MAST Search Tools provides search tools and retrieval support for the following missions MAST Scrapbook Missions Catalogs amp Surveys What s New oe tee HST ASTRO ORFEUS Copemicus SDSS FAQ FUSE HUT BEFS ROSAT GSC IUE UIT IMAPS DSS Prepared Datasets EUVE WUPPE TUES VLA FIRST Software ELLS Cross correlation Target Search Related Sites and or Mission Search Acknowledgments i Enter Target name or Coordinates I and or Data Type s Extreme Far Near Near x Ray uv uv uv Optical IR Radio Images amp zg E 5 g E t Spectra Other Search Reset Help Top of Page printer friendly page archive stsci edu opyright Notice http stdatu stsci eduwindex htral Modified Jun 26 2001 17 11 s Cc INTRO 1 20 Chapter 1 Getting HST Data ___ Figure 1 7 HST Archive Web search Form jes 2 42a 883 8 Back Forward Reload Home Search Netscape Print Security Shop Stop N j wA Bookmarks Location http archive stsci edu cgi j WebMail g Radio bin hst
286. nds on the pattern The target field is always contained in the assoc_id0_mos fits file Patterns which involve chopping onto the sky to produce background refer ence images result in multiple assoc_idn_mos fits files after pro cessing through calnicb with the background positions identified by n to 8 3 Mosaicing calnicb J NICMOS 3 19 One assoc_idn_spt fits support file for each assoc_idn_mos fits file created 3 4 3 Processing The basic philosophy of the calnicb algorithm is to remove the background from each image after source identification to align the images by calculating offsets and to produce the final mosaic The processing steps of calnicb can be summarized as follows 1 2 3 4 5 6 7 Read the input asn table and input images Determine processing parameters from keyword values Combine multiple images at individual pattern positions Identify sources in the images Estimate and remove the background signal Create a mosaic image from all pattern positions Write the output association table and mosaic images The sections below discuss steps 2 through 6 in greater detail Processing Parameters Header keywords from the input _cal fits images are read and evaluated in order to guide the calnicb processing One set of keywords table 3 3 pertains to the association as a whole and therefore are read only once from the first input member image Table 3 3 Keywords Common to all D
287. ne or both parallel cameras If an observation was made with all three cameras running in parallel using the same readout sequences then there usually are no bars present in the data because there is no collision between camera readouts and parallel detector autoflush The bars run along the slow readout direction i e along columns in NIC1 and along rows in NIC2 and NIC3 Normally there is only one bar per quadrant but occasionally there are more always reflected in all 4 quadrants Sometimes the bars will be in sync appearing at the same place in successive readouts Other times they may appear in alternate readouts or their positions may vary from readout to readout sometimes appearing to march across the frame over the course of a MULTIACCUM sequence They typically run the length of a quadrant 128 pixels and are 3 pixels wide The first pixel is lower than the mean the second is at the mean level and the third is higher than the mean giving the impression of an undersampled sinusoidal spike with an amplitude of up to 10 DN peak to peak The bars are almost always broken in at least one place with a shift of 2 10 pixels in the narrow direction Cures The bars are noiseless localized changes in detector bias The amplitude is usually quite low and for some observers they may have little impact on science data However it is possible to correct bars during post processing One approach is to flag pixels affected by bars in the d
288. nen h 2 12 2 3 1 Converting FITS to GEIS eessen 2 13 2 3 2 GEIS Data Groups iss cpes crccsetesgcetscniothtanesaseteseuetiecness 2 14 2 3 3 Working with GEIS FileS ceeeeeeeeeeeeeeeeees 2 15 2 3 4 The waiver FITS format ccccssseeeeeeeeeeeees 2 17 Chapter 3 STSDAS Basics 3 1 3 1 Navigating STSDAS 0 0 0 0 ee eeeeeeeeeeeeeeeeeees 3 2 3 1 1 STSDAS Structure eee cere vese ietces esterteceaceeet eek 3 2 3 1 2 Packages of General Interest eeeeeeeees 3 2 3 2 Displaying HST Image cceeeeeeeeeteeeeeteeees 3 4 3 2 1 The display TASK cfecccccieieycelerebepeeccercesnts resenebteneses 3 5 3 2 2 Working with Image Sections eeeeeeeees 3 8 3 3 Analyzing HST Images ccceeeeeeeeeeeeeseeeeees 3 9 3 3 1 Basic ASMOMEGUY scisiscceiiivisaetececsssbencatvietoadelanceaecd 3 10 3 3 2 Examining and Manipulating Image Data 3 12 3 3 3 Working with STIS ACS and NICMOS Imsets cccceccesecceeeeeeeeeeeeeeeeeeeeseaeeeeeeens 3 14 3 3 4 Photometry iecaves cr esadtcadtanvaxivdua saedecelisauenttimiagadecagedadds 3 17 3 4 Displaying HST Spectra 00 0 0 eceeeeeeeeeeeeees 3 20 3 4 1 FOS and GHRS Spe ctra cccccsscccccccccseeeeeeeeeeees 3 20 3 4 2 STIS Spectra ais ci cesiiadecsvsvi vie veelececessstvhvagaesagesasds 3 21 3 4 3 Producing Hardcopy seis ciieveneoceccecaniiaiimivinanve 3 22 3 5 Analyzing HST Spectra cccececeeeeeeeeeeeeees 3 24 3 5 1
289. ng conversion to count rate and CRIDCALC cosmic ray processing You then take first differences with sampdiff displays them as a mosaic with mosdisplay to look for bars bias jumps monster cosmic rays or other oddities in individual readouts and then use pstats to plot the median count rate units rate per sample time in the image quadrant 1 128 1 128 Having satisfied yourself that the data is fine you might then complete processing using the biaseq and pedsky tasks in the following manner The NICMOS History Tool HJ NICMOS 5 5 ni gt biaseq n4xjl3jwq_ima fits n4xj13jwq_beq fits gt gt gt skysamps 1 13 fitbias fitjump ni gt nicpipe n4xj13jwq_beq fits stage final ni gt pedsky n4xjl3jwq beq cal fits n4xjl3jwq ped fits gt gt gt salgorithm auto interactive rmedian In this case you have corrected readout to readout bias drifts with biaseq also fitting for bias jumps in the process and then carried out the final pedestal correction with pedsky solving for the background level and pedestal interactively Please see section 4 1 5 of this manual and the on line help files for biaseq and pedsky for a detailed explanation of the parameters The resulting end product image will be n4xj13jwq_ped fits 5 2 The NICMOS History Tool When reducing and analyzing NICMOS data it is sometimes important to know certain aspects about the instrument or telescope history at the time the observations were
290. nt Handbook The reference dark file appropriate for the exposure sequence used in MULTIACCUM or the exposure time and NREAD values used in ACCUM is determined by the OPUS generic conversion process when it populates the DARKFILE reference file keyword in the primary header of NICMOS 3 12 Chapter 3 Calibration raw data files The calnica DARKCORKR step subtracts the dark reference images readout by readout for MULTIACCUM observations from the science data Error estimates of the dark current stored in the ERR images of the DARKFILE are propagated in quadrature into the ERR images of all processed science imsets Data quality DQ flags set in the DARKFILE are also propagated into the DQ images of all processed imsets For BRIGHTOBJ mode data dark subtraction is skipped by default in calnica because in general the short exposure times should result in insignificant dark current relative to the object signal In practice there may be bias components with non zero amplitude e g akin to shading which are present in BRIGHTOBJ mode data At present however there is no standard procedure for removing these Given the very limited use of BRIGHTOBJ mode for on orbit science we will not discuss its reduction further here Chapter 4 includes a more detailed discussion of NICMOS dark and bias components their properties and behavior including irregulari ties which are not well handled by the standard processing pipeline and wh
291. nto that pixel The latter is not known until the location of the dispersed source has been specified and therefore the flatfielding cannot be done in advance It is omitted during 2 dimensional data processing through calnica Later after 1 dimensional spectra have been extracted from the grism images a wavelength dependent correction for QE variations is applied see section 5 8 2 NICMOS 5 48 Chapter 5 Data Analysis 5 8 1 The wavelength calibration for the extraction of spectra requires a direct image corresponding to each grism image If individual exposures for the grism images are co added before extraction a similar co addition should also be performed for the direct images in order to maintain the relative position of objects in the direct image with the corresponding spectrum in the grism image If grism and direct images are processed separately by calnicb this relative registration is in general not maintained An IRAF package nictools which helps to co add direct and grism images is available from the ST ECF nictools web site The package includes tasks to create association files makeasn find relative shifts from direct images and apply them to grism images alignasn and combine associated images with those fits applied asncombine This package can be used to prepare images for the extraction of the spectra In general combining dithered grism images before extracting spectra is probably not a good idea wheneve
292. o its basic search and retrieval function StarView allows users to cross qualify results from separate searches of the HDA and to export the results of searches to disk as ASCII files These operations are performed with the XQual and Export buttons respectively As an example of cross qualification a user might want to identify all the spiral galaxies for which both WFPC2 images and STIS spectra have been obtained This could be accomplished with the Cross Qualification feature by first doing two separate Quick Searches in which these respective instruments are specified in the query box and in which Galaxy Spiral is typed in the Target Description box for both searches Clicking the XQual Getting Data with StarView IJ INTRO 1 11 button specifying Target Name as the common field in the two sets of search results as shown in figure 1 5 and clicking the X Qualify button then identifies the galaxies occurring in both lists StarView then places these galaxy names in the Target Name box of a new Quick Search window Clicking the Search button with WFPC2 STIS entered for Instrument then gives a list of all the WFPC2 and STIS datasets for these galaxies The Cross Qualification function can also be performed on the files produced by the Export feature Figure 1 3 Results of StarView search for WFPC2 OTFR calibration files for M87 ile Edit View mhes Comment Window HSS nter qualifications for WFPC2 OTF
293. old multiple images each with associated parame ters This feature allowed the packaging of images from the four WF PC 1 chips into a single unit as well as the packaging of multi ple FOS or GHRS readouts into single files OIF files and early FITS files could contain only single images FITS File Format W INTRO 2 3 e GEIS data are stored in two parts an ASCII header and a binary data file The separation of these two pieces and the restriction of the header to ASCII made these headers easier to read and print in the days when computers were less powerful and tasks for reading header information were less numerous OIF headers combine ASCII and binary information and FITS headers come packaged with the data in a single file GEIS was also the standard format for archiving and distribution of HST data until September 1994 when the Space Telescope Data Archive and Distribution Service ST DADS came online This new system stores and distributes HST data files in machine independent FITS format but observers with FOC FOS FGS GHRS HSP WEF PC 1 and WFPC2 still must convert their files to machine dependent GEIS format as described in section 2 3 1 before using IRAF STSDAS software see chapter 3 in the HST Introduction to reduce their data Since the selection of GEIS as HST s standard data format FITS has added features that have dramatically increased its flexibility In particular FITS files can now contain multiple image extensi
294. om the input datasets All the datasets must have been processed through the basic pipeline data reduction calnica before being processed through calnicb In addition to the output science image s calnicb produces another association table _asc fits which has the same content as the _asn fits table along with additional information on the offsets used by the pipeline for reconstructing the science image and background values computed for each image For mosaics dither patterns there is only one final image produced with file name 0_ mos fits For chop patterns in addition to the background subtracted image of the target 0_mos fits an image for each background position is produced the file names of these background images are 1_mos fits 2 mos fits 8 mos fits a maximum of eight independent background positions is obtainable with the NICMOS patterns see the NICMOS Instrument Handbook for details Support File The support files spt fits contain information about the observation and engineering data from the instrument and spacecraft that was recorded at the time of the observation A support file can have multiple FITS image extensions within the same file in the case of a MULTIACCUM observation there will be one extension for each readout i e each imset in the science data file Each extension in the support file 1 Observation Support amp Post Observation Data Processing Unified Systems NICMOS 2 10 C
295. on Failure The guide star acquisition at the start of the observation set could fail if the FGS fails to lock onto the guide star The target may not be in the aperture or maybe only a piece of an extended target is in the aperture The jitter values will be increased because FINE LOCK was not used The following list of cmh header keywords indicate that the guide star acquisition failed V3_RMS 19 3 V3 Axis RMS milli arcsec V3_P2P 135 7 V3 Axis peak to peak milli arcsec GSFAIL DEGRADED Guide star acquisition failure The observation logs for all of the following observations in the observation set will have the DEGRADED guide star message This is not a Loss of Lock situation but an actual failure to acquire the guide star in APP C 12 Appendix C Using Observation Logs the desired guiding mode For the example above the guiding mode dropped from FINE LOCK to COARSE TRACK GUIDECMD GUIDEACT FINE LOCK 1 Commanded Guiding mode COARSE TRACK Actual Guiding mode at end of GS acquisition If the observational dataset spans multiple orbits the guide star will be re acquired but the guiding mode will not change from COARSE TRACK In September 1995 the flight software was changed so that COARSE TRACK is no longer an option The guiding mode drops from two guide star FINE LOCK to one guide star FINE LOCK or to GYRO control C 3 3 Moving Targets and Spatial Scans
296. ons each with its own header size and datatype that allow multiple exposures to be packaged into the same file along with associated error and data quality information The FITS image kernel in IRAF version 2 11 released in August 1997 enables users to access FITS image extensions in ways similar to how they would access GEIS data groups Because of these advantages FITS was chosen as the standard reduction and analysis format for STIS and NICMOS The STSDAS tasks written for these instruments expect FITS files as input and produce FITS files as output You cannot convert STIS and NICMOS files to GEIS format Observers using these instruments should therefore read the following section which explains how to work with these new FITS files 2 2 FITS File Format Flexible Image Transport System FITS is a standard format for exchanging astronomical data between institutions independent of the hardware platform and software environment A data file in FITS format consists of a series of Header Data Units HDUs each containing two components an ASCII text header and the binary data The header contains a series of header keywords that describe the data in a particular HDU and the data component immediately follows the header The first header in a FITS file is known as the primary header and any number of extensions can follow the primary HDU The data unit following the primary header must contain either an image or no data at all but ea
297. ope assembly OTA resulting from the telescope warm up and cool down during an orbital period These short term focus variations are usually referred to as OTA breathing HST breathing focus breathing or simply breathing 6 NICMOS Instrument Science Report NICMOS ISR 98 015 Coronagraphic Reductions J NICMOS 5 41 During Cycle 7 and 7 5 the NICMOS dewar anomaly caused the coronagraphic hole to migrate to different locations on the detector The position of the hole on the detector had been observed to move as much as 0 25 pixel in three orbits The movement of the hole was found not to be uni directional but rather the hole jitters back and forth along an X Y diagonal by as much as 0 5 pixel The direct subtraction of two unregistered coronagraphic images that were not obtained back to back in the same orbit with a change in roll can yield large residuals Coronagraphic images need to be subpixel shifted and or convolved with a Gaussian function to match the observed PSF before subtraction The following discussion applies both subpixel shifting and Gaussian convolution reduction techniques to two F110W filter images from the NICMOS calibration program 7052 The data used in the examples below are n45j22lam and n45j23mym The data were obtained in consecutive orbits with a spacecraft roll of 36 between orbits Subpixel Shifting The images to be subtracted must be registered to sub pixel accur
298. or Sources effect in many discussions of NICMOS data although we note here that the term pedestal has also been applied to other aspects of NICMOS array behavior The variable quadrant bias is usually constant over a given array quadrant but different from one quadrant to another Its amplitude varies from readout to readout sometimes drifting gradually but occasionally with sharp changes from one readout to another not always seen in all quadrants simultaneously On 22 August 1997 a modification was made to the NICMOS flight software which reduced but did not eliminate the pedestal effect Data taken before that date is in general severely affected by variable bias levels and requires careful handling in order to achieve high quality data reductions However essentially all NICMOS data even after the flight software change are impacted by pedestal to one degree or another The variable quadrant bias has two major effects on NICMOS MULTIACCUM data The first and generally less important effect is that the signal in a given pixel which should normally accumulate linearly with time over the course of an integration after other sources of bias and dark current are removed and when intrinsic array non linearity is corrected can instead vary irregularly as the bias level in a quadrant changes underneath the astronomical signal from source background The CRIDCALLC step of the calnica pipeline fits a linear ramp counts vs time
299. or continuum fitting Displaying and redrawing spectra Z Expand and autoscale data range between cursor positions Set plot base level to zero Clear all windowing and redraw full current spectrum Redraw spectrum with current windowing Window the graph Etch a sketch mode connects two cursor positions Overplot standard star values from calibration file Zoom graph by a factor of two in X direction Switch between physical pixel coordinates and world coordinates General file manipulation commands Display help Get another spectrum Write current spectrum to new or existing image Quit and go on to next input spectrum INTRO 3 34 Chapter 3 STSDAS Basics 3 5 4 STSDAS fitting Package The STSDAS fitting package contains several tasks as listed in table 3 7 for fitting and analyzing spectra and images The ngaussfit and nfitld tasks in particular are very good for interactively fitting multiple Gaussians and nonlinear functions respectively to spectral data These tasks do not currently recognize the multispec WCS method of storing wavelength information They recognize the simple sets of dispersion keywords such as WO WPC and CRPIX CRVAL and CDELT but these forms apply only to linear coordinate systems and therefore would require resampling of your data onto a linear wavelength scale first However these tasks do accept input from STSDAS tables in which you can store the wavelength and
300. or point sources especially for short wavelength in focus NIC3 observations many dither positions gt 10 are probably needed before the error on the mean count rate is smaller than other sources of photometric uncertainty in NICMOS Camera 3 intrapixel sensitivity variations can have a major impact on photometry of point sources For data taken with fewer than 10 dither positions this uncertainty may dominate photometric errors unless steps are taken to correct it We strongly recommend that Camera 3 users concerned with photometry of point sources read the references cited here Temporal and Spatial PSF and Focus Variations The point spread function PSF of HST changes with time and these changes will affect photometry using small apertures Changes in focus observed on an orbital timescale are due mainly to thermal breathing of the telescope In addition there were long term variations in NICMOS focus as the cryogen evaporated and the dewar relaxed The solid nitrogen introduced stress on the instrument and NICMOS detectors moved along the focus direction as this stress diminished The change was especially rapid during the SMOV period The focus was largely stable thereafter however throughout most of the instrument lifetime The dewar distortion had the greatest effect on the focus of Camera 3 pushing it beyond the range of the Pupil Alignment Mechanism PAM For this reason two special Camera 3 refocus campaigns each
301. ords redundantly into each extension header You can suppress keyword inheritance by using the NOINHERIT keyword in the file specification For example im gt imcopy fitsfile fits 6 noinherit outfile fits im gt imcopy fitsfile fits sci 2 noinherit outfile fits Both of the preceding commands will create an output file whose header contains only those keywords that were present in the original extension header Note that in the second command the noinherit specification is bracketed with the EXTNAME and EXTVER keywords and not in a separate bracket of its own as in the first command where an absolute extension number is used For a complete explanation of FITS file name specifications see http iraf noao edu iraf web docs fitsuserguide html Appending Image Extensions to FITS Files IRAF STSDAS tasks that produce FITS images as output can either create new FITS files or append new image extensions to existing FITS files You may find the following examples useful if you plan to write scripts to reduce STIS ACS or NICMOS data If the specified output file does not yet exist a new output file is created containing only a primary HDU if no specification is appended to the output file name For example to copy the contents of the primary header of fitsfile fits into the primary HDU of the FITS file outfile fits type the command cl gt imcopy fitsfile fits 0 outfile fits If the specified output file alrea
302. ou must use the parkey task on the _asn fits 1 file As an example to change the ILLMFILE type parkey path name_ilm fits data_asn fits 1 ILLMFILE where path name_ilm fits is the full name and path to the ILLMFILE and data_asn fits is the association table you are editing In order to set ILLMCORR to OMIT and skip this processing step entirely type par key OMIT data_asn fits 1 ILLMCORR NICMOS 3 28 Chapter 3 Calibration CHAPTER 4 Anomalies and Error Sources In this chapter 4 1 NICMOS Dark Current and Bias 4 3 4 2 Bars 4 20 4 3 Detector Nonlinearity Issues 4 21 4 4 Flatfielding 4 24 4 5 Pixel Defects and Bad Imaging Regions 4 26 4 6 Effects of Overexposure 4 30 4 7 Cosmic Rays of Unusual Size 4 37 4 8 Scattered Earthlight 4 39 The previous chapter described the basic stages of NICMOS pipeline processing As with any instrument however high quality data reduction does not end with the standard pipeline processing NICMOS data are subject to a variety of anomalies artifacts and instabilities which complicate the task of data reduction and analysis Most of these can be handled with careful post facto recalibration and processing which usually yields excellent scientific grade data reductions Careful NICMOS data processing usually requires a certain amount of hands on interaction from the user who must inspect for data anomalies and treat them accordingly during the reduc
303. out sequence ni gt sampinfo n4yx23x0q_ raw fits This will produce a table of output information that looks like this IMAGE NEXTEND SAMP_SEQ NSAMP EXPTIME n4ux23x0q_raw fits 125 SPARS64 25 1407 933 IMSET SAMPNUM SAMPTIME DELTATIME 1 24 1407 933 63 997 2 23 1343 936 63 997 3 22 1279 939 63 997 21 4 127 990 63 997 22 3 63 993 63 388 23 2 0 605 0 302 24 1 0 302 0 302 25 0 000 0 000 NICMOS Dark Current and Bias IJ NICMOS 4 19 We see that the readouts with linearly spaced DELTATIME values SAMPNUMs 4 through 24 are in imsets 1 to 21 The last readout imset 1 often has bias jumps see Bias Jumps or Bands on page 4 10 so we may want to exclude it when feeding the desired range of sky samples to biaseq for use in constructing the clean sky image So ni gt nicpipe n4yx23x0q_raw fits stage biaseq ni gt biaseq n4yx23x0q_ima fits n4yx23x0q_beq fits gt gt gt skysamps 2 21 fitbias fitjump The output image n4yx23x0q_ beq fits has been corrected for non linear bias drifts and for spatial bias jumps as well Next we complete the pipeline processing using nicpipe doing the FLATCORR UNITCORR CRIDCALC steps to prepare for pedsky ni gt nicpipe n4yx23x0q_beq fits stage final We now run pedsky non interactively letting it fit for the sky level and four quadrant biases on its own ni gt pedsky n4yx23x0q beq ima fits n4yx23x0q ped fits gt gt gt
304. ove the assumed uniform constant sky level S The impact of these sources is minimized however by using sigma clipped statistics which exclude pixels with strongly deviant values e g those due to actual astronomical sources bad pixels etc Additionally the user may apply a ring median filter to the image when computing X This can effectively remove compact or point like sources and may help the task perform better for moderately crowded fields but considerably slows the computation speed The user may wish to experiment by trying pedsky both with and without the ring median option In practice a certain amount of source noise contribution to X is tolerable to the pedsky algorithm It acts as an offset to the amplitude of X but generally has no effect on the location of the minimum value for X relative to S or B4 1 This is a change from earlier versions of the pedsky task and earlier editions of this Handbook Previously pedsky required a partially processed image and would not work on flatfielded data NICMOS Dark Current and Bias IJ NICMOS 4 17 Pedsky works in both interactive and non interactive modes Alternatively the user can supply a sky value to be subtracted in which case the remaining quadrant dependent pedestal is estimated and subtracted After pedsky processing the remaining standard calibration steps including flatfielding can then be easily applied using another call to the script nicpipe Note that
305. ovided the task defaulted to the first group To reveal more information regarding group 10 you can type cl gt imhead indata hhh 10 long page which will generate a long listing of both the ASCII header parameters in the hhh file and the specific group parameters for group 10 from the hhd file Other Group Related Tasks Currently IRAF or STSDAS tasks cannot process all the groups in an input image and write the results to corresponding groups in an output image However there are several STSDAS tasks particularly in the toolbox imgtools and hst_calib ctools packages that simplify working with group format data Please refer to chapter 3 and the STSDAS User s Guide for more details about working with GEIS images The waiver FITS format Although waiver is not quite the accurate or good word for the intended purpose for historic reasons it has stuck and will be reluctantly adopted However in the past a grammatically incorrect word waivered had been used The waiver FITS format was developed when the HST archive needed a format to store and distribute the data products in a machine independent medium for the community at a time before FITS image extension was standardized As a result the waiver FITS format was adopted as a compromise Since at the time FITS could only have a single image while the HST data in GEIS format may have several images as multiple groups in one file the idea
306. ow If you have multiple exposures in an orbit you may wish to consider trying this but at present there is no general software available for doing this procedure Because the CR persistence pattern remains fixed in successive exposures you may also use the first exposure in the orbit to create a mask for setting the affected pixels to zero weight when combining the images In HST Cycle 11 when NICMOS is revived STScI will automatically schedule special dark exposures after SAA passages in order to provide a map of the CR persistence Software for implementing this persistence correction will be written and tested as soon as possible after SMOV3B when the NCS is installed Amplifier Ringing The Mr Staypuft Anomaly There is another sort of NICMOS ghost image wholly separate from those induced by persistence Bright targets which appear in a given detector quadrant can produce an electronic ringing effect in the readout amplifiers which may induce ghost images at the same pixel locations in the other three quadrants This is believed to be due to the pull down of the power supply which does not completely recover from reading a large number by the time it s asked to read the next number from the next quadrant In some cases a whole row or column whichever direction the fast read clocking runs can be anomalously high The amplitude of the ghost images is of order a tenth of a percent of the real image count rate Inside the STScI
307. particular feature or features that you want to fit You may then want to Analyzing HST Spectra W INTRO 3 35 e Define a sample region using the cursor mode s command over which the fit will be computed so that the task will not try to fit the entire spectrum e Define an initial guess for the baseline coefficients by placing the cur sor at two baseline locations one on either side of the feature to be fitted using the B keystroke e Use the R keystroke to redraw the screen and see the baseline that you ve just defined e Set the initial guesses for the Gaussian centers and heights by placing the cursor at the peak of each feature and typing e e Press F to compute the fit once you ve marked all the features you want to fit The results will automatically be displayed You can use the show command to see the coefficient values Note that when the ngaussfit task is used in this way i e starting with all default values the initial guess for the FWHM of the features will be set to a value of one Furthermore this coefficient and the coefficients defining the baseline are held fixed by default during the computation of the fit unless you explicitly tell the task through cursor colon commands to allow these coefficients to vary It is sometimes best to leave these coefficients fixed during an initial fit and then to allow them to vary during a second iteration This rule of thumb also applies to the setting
308. pending on the camera in each readout of the MULTIACCUM observation and identifies those with median signals more than 20 different from the surrounding columns or rows as containing a bar The user can set a different bars detection threshold by using the barthresh task parameter for calnica It flags these pixels with a data quality value of 256 bad pixel detected during calibration in the DQ array of the appropriate imsets In the subsequent CRIDCALC calibration step where the data from all readouts is combined the flagged pixels are rejected so that the final combined image _cal fits file will be free of the bars No reference file is used by this step BARSCORR is available only in version 3 3 and higher of calnica which was released after the end of NICMOS operations and instru ment warm up Therefore all Cycle 7 and 7N NICMOS data retrieved P from the HST archive before 26 September 2001 were processed with out the BARSCORR step In order to take advantage of this step you will need to recalibrate your data or to retrieve them again from the Archive using OTFR FLATCORR Flat Field Correction In this step the science data are corrected for variations in gain between pixels by multiplying by an inverse flatfield reference image This step is skipped for observations using a grism because the flatfield corrections are wavelength dependent This step uses the FLATFILE reference file which contains the flatfield imag
309. pipeline e g calibration steps performed and reference files used and the properties of the data themselves e g number of image extensions dimensions and data type of each image coordinate system information flux units and image statistics The primary header carries global keywords which are applicable to all extensions The extension headers carry extension specific keywords which contain information relevant to the image in a particular extension For example observation parameters calibration switches and reference file names are contained in the primary header Exposure time and World Coordinate System information on the other hand are contained in the header of each image extension because this information could vary from one set of extensions to another Table 2 3 below lists most of the keywords in the primary header of the science data files The entries in this table are appropriate for data retrieved now from the HST Archive via on the fly reprocessing OTFR see chapter 3 Some header keywords in older NICMOS data may be different In Header Keywords W NICMOS 2 11 particular the observing pattern keywords have been changed for Cycle 11 and the dictionary below describes the new keyword format In addition the tables list the SAA keywords that will be used with the new post SAA darks to be taken in Cycle 11 For data taken in Cycle 7 and 7N these keywords will not be populated The STScI Data Processing Team main
310. pixels of a quadrant are read Visually this appears as a ripple and a signal gradient across a given quadrant of an uncorrected image figure 4 2 The amplitude of the shading can be as large as several hundred electrons across a quadrant in NIC2 with smaller amplitudes in NIC1 and NIC3 The shading exhibits all the characteristics of a bias change including lack of noise The shading signal is not the same for each readout but depends primarily on the time interval since the last readout not reset of a pixel For each readout in a NICMOS MULTIACCUM sequence this time interval is recorded in the FITS header of each imset by the keyword DELTATIM If the time A between reads remains constant the bias level introduced by the shading remains constant but if Ar varies e g logarithmically as in some MULTIACCUM sample sequences then the bias level changes with each successive read and thus the overall shading pattern evolves throughout the sequence Figure 4 2 Examples of shading for NICMOS cameras 1 2 and 3 ide A a Sa CRS IN cet a ae wae M ak iat Meg bret ZI ARN AGIAN is tS EH NIC1 In addition to the DELTATIM dependence the shading amplitude and shape also depend on the mean temperature of the detectors which slowly warmed as the cryogen sublimated over the lifetime of the instrument Subtle temperature changes during a MULTIACCUM exposure can also lead to shading changes A sequence with many long DELTATIMEs such as a
311. poffsets specplot noao onedspec Multispec image Stack and plot multiple spectra splot noao onedspec Multispec image Plot and analyze spectra amp image lines see splot on splot page 3 31 The splot task in the IRAF noao onedspec package is a good general analysis tool that can be used to examine smooth fit and perform simple arithmetic operations on spectra Because it looks in the header for WCS INTRO 3 32 Chapter 3 STSDAS Basics wavelength information your file must be suitably prepared Like all IRAF tasks splot can work on only one group at a time from a multigroup GEIS file You can specify which GEIS group you want to operate on by using the square bracket notation for example cl gt splot yOcy0108t clh 8 If you don t specify a group in brackets splot will assume you want the first group In order to use splot to analyze your FOS or GHRS spectrum you will first need to write the wavelength information from your c Oh file to the header of your clh files in WCS using the mkmultispec task see mkmultispec on page 3 25 The splot task has many available options described in detail in the online help Table 3 6 summarizes a few of the more useful cursor commands for quick reference When you are using splot a log file saves results produced by the equivalent width or de blending functions To specify a file name for this log file you can set the save_ file parameter by typing for example
312. ppendix B All of the infor mation contained in the old cmh jih ASCII header is now available as keywords in the FITS files e rootnamej_jit fits The FITS file containing the table informa tion The comments for the _jif file apply here as well Table C 2 Contents of cmj Table Appendix C Observation Log Files W APP C 5 Parameter Units Description seconds seconds Time since window start V2 dom arcseconds Dominant FGS V2 coordinate V3 dom arcseconds Dominant FGS V3 coordinate v2 roll arcseconds Roll FGS V2 coordinate V3 roll arcseconds Roll FGS V3 coordinate SI v2 arcseconds Jitter at aperture reference SI V3 arcseconds Jitter at aperture reference RA degrees Right ascension of aperture reference DEC degrees Declination of aperture reference Roll degrees Angle between North and V3 DayNight 0 1 flag Day 0 or night 1 Recenter 0 1 flag Recentering status TakeData 0 1 flag Vehicle guiding status SlewFlag 0 1 flag Vehicle slewing status APP C 6 lf Appendix C Observation Log Files Figure C 1 A Representative jih or cmh Header aSIMPLE BITPIX DATATYPE NAXIS NAXIS1 NAXIS2 GROUPS GCOUNT PCOUNT PSIZE OMS_VER PROCTIME O O O a O a a S CRVAL1 CRVAL2 CRPIX1 CRPIX2 CTYPE1 CTYPE2 cD1_1 cD1_2 cD2_1 cD2_2 COORDSYS XPIXINC YPIXINC PARITY BETA1 BETA2 C a a a O a O O a PROPOSID PROGRMID OBSET_ID OBSERVTN TARGNAME STARTIME ENDTIME SOGSID CONFIG PRIMARY OPERATE TLMFORM AP
313. ption of the task Typing help package will produce one line descriptions of each task in the package Finding Tasks There are several ways to find a task that does what you need e Use help package to search through the IRAF STSDAS package structure e Use the apropos task as shown in figure A 4 to search the online help database This task looks through a list of IRAF and STSDAS pack age menus to find tasks that match a specified keyword Note that the name of the package containing the task is shown in parentheses e Ask more experienced user who can usually point you in the right direction Appendix A IRAF Basics J APP A 9 Figure A 4 The apropos task Using apropos E STSDAS ct gt apropos WCS wcslab Overlay a displayed image with a world coordinate grid lt cl images tv Look for Tasks Dealing wcsedit Edit the image coordinate system lt cl proto z 5 wesreset Reset the image coordinate system cl proto with World Coordinates makewcs Write the ICS on the image header based on the plate sol stsdas a nalysis gasp weslab Produce sky projection grids for images stsdas graphics stplot wlpars Pset to specify characteristics of WCS labelled graphs stsdas gra phics stplot wespars Pset to specify a WCS stsdas graphics stplot mkmultispec Combine wavelength and data with the MULTISPEC MWCS lt stsdas hst_c A 2 4 Setting Parameters Parameters specify the input information for IRAF tas
314. r exposure level page The content of the pages is as follows Visit Level Pages e Cover Page contains the proposal ID the visit number the PI s last name and the proposal title e Explanatory Notes a set of notes explaining the information con tained in the paper products Target List a table listing the targets of the observations being sum marized e Observation Summary a table summarizing the proposal informa tion for each exposure in the present set including processing and data quality flags Optional Parameters a table listing the optional parameters other than the pattern related parameters used in the observations e Observing Pattern Strategy a table listing the observing pattern used for each exposure in the set Paper Products IJ NICMOS 2 23 Exposure level Pages Final Calibrated Image a grey scale plot of the calibrated science image a mosaic if the observation was dithered Observation Parameters several useful parameters are listed on the right hand side of a subset of the paper product pages Observation root name the date and time of the observation the target name and position the instrument configuration FOM offset and pattern dither and chop information is given Spacecraft Performance known problems with guide star acquisi tion spacecraft guidance recenterings and telemetry drop outs are listed as are detected problems with the instrument s operation e g Take D
315. r it can be avoided As noted above every pixel on the array has a different spectral response Combining dithered grism images before extraction will combined data from dif ferent pixels making it difficult or impossible to reliably flux calibrate the resulting spectrum In general we recommend that individual spectral and direct image pairs be reduced and the resulting spectra combined when the individual spectra are strong enough Extraction Software Detailed software manuals and descriptions of the extraction algorithms can be found at the above URLs Only a brief summary is given below Input Files The extraction software requires two types of input images one for object finding and one which contains the spectra to be extracted Typically the former is a direct image of the target field obtained with one of the NICMOS continuum filters preferably at a wavelength within the range covered by the grism However the grism image itself can also be used for object finding e g on the zeroth order spectra The image which contains the spectra is assumed to be not flatfielded which is the default in calnica The input files can be either the output of calnica _cal fits or the mosaiced images created with calnicb _mos fits The software also reads FITS images without the NICMOS specific extension but some functionalities which depend on the error planes _cal fits err or data quality flags _cal fits dq will not be avai
316. r uncompressing and extracting the tar files see below you need to unpack the FITS files as described below The synthetic photometry data are read in similar way as the instrument datasets using the script unpack cl_ provided in the top directory This script is run within IRAF to convert data from FITS format into the format used by the synphot task This script assumes you have the logical V Appendix A Getting IRAF and STSDAS W APP A 17 crrefer set up in your extern pkg file which is in the directory Siraf unix hlib Unix or iraf vms hlib VMS or have it set up in your session You do this by placing the command below in extern pkg or by typing it on the command line set crrefer node partition stdata synphot Figure A 7 shows how to convert the files Figure A 7 Unpacking Synthetic Photometry Files cl Just in case cl gt cd node partition stdata synphot cl gt set crrefer node partition stsdata synphot cl gt task unpack unpack cl cl gt tables ae ta gt fitsio i The is used because the task fi gt unpack has no parameter file Note that all three synphot files must be unloaded for the script to com plete successfully A 3 3 Extracting the synphot Unix Tar Files If you retrieved the synphot database as compressed tar files you will need to copy them to an appropriate subdirectory and then expand and unpack the files The tar and compress utilities that do this are are
317. raints specified by the user based on the wavelength region of interest and will provide hypertext links to these datasets If only HST datasets are desired they can be accessed separately by clicking HST on the MAST home page 3 European archive users should generally use the ST ECF Archive at http archive eso org Canadian users should request public archival data through the CADC web site at http cadcwww dao nrc ca Proprietary data are only available through STScI Reading HST Data Tapes and Disks IJ INTRO 1 17 The HST section of MAST offers tutorials about the HDA as well as a FAQ page and HDA news It also provides links to HST Prepared datasets such as the Hubble Deep Field images Clicking on the Main Search Form option of the HST section brings up the page shown in figure 1 7 Here the user is queried for the same search parameters as requested by StarView e g Object Name Instrument and Proposal I D Once these are entered clicking the Search button returns a page listing the datasets found which can then be selectively marked for retrieval The data type and retrieval options remain the same as those for StarView Previews of GIF files of the datasets are also available 1 4 Reading HST Data Tapes and Disks If you request HDA files on tapes or disks you will receive them within a few weeks of your request The tapes will contain tar files containing the requested datasets The datasets will all be in FIT
318. rchive however empirical PSFs for the central regions of the detectors can be obtained from the calibrated images obtained for the Cycle 7 absolute photometry proposal 7691 and photometric monitoring proposal 7607 programs The STScI NICMOS group will make a library of empirical PSFs available at some time in the future 2 TinyTim software can be retrieved from the Web at http www stsci edu software tinytim tinytim html NICMOS 5 16 JJ Chapter 5 Data Analysis Out of Band Leaks Many very red targets e g protostars were observed with NICMOS at short wavelengths 1 um For these sources the flux at 2 2 2 5 um could be orders of magnitude larger than at 1 0 um and therefore exceptionally good out of band blocking would be required Pre launch tests indicated that for very red sources temperature 700 K and lower some NICMOS filters might have significant red leaks The suspect filters were F090M FO95N FO97N F108N F110M F110W F113N F187N and F190N A limited set of in flight tests in calibration programs 7691 and 7904 were made during Cycle 7 observing very red stars to calibrate the possible effects of out of band leaks These data have never been carefully analyzed but preliminary indications are that actual red leaks are insignificant or non existent We nevertheless caution here that this analysis is only preliminary Users interested in photometry of sources with extreme colors should check the STScI NICMOS
319. rcing the stage to be skipped The dummy reference files must be present however in order for calnicb processing to proceed Combination of Multiple Exposures If there is more than one image at any pattern position NUMITER gt 1 the multiple images at each position are first registered and then combined into a single image The coordinates as determined by the WCS keywords of the first image at a given pattern position are used as a reference for the registration The offsets to all other images at that pattern position are first computed by comparing their WCS data and then refined using a cross correlation technique down to a level of 0 15 pixels The cross correlation technique employes an algorithm which minimizes the differences between fluxes in the images The computed offsets in units of pixels are recorded in the output association table After determining the relative offsets the images are aligned using bilinear interpolation and are then combined on a pixel by pixel basis The combined pixel values are computed as a weighted mean of all unflagged i e DQ 0 samples using the input image ERR values as weights If three or more samples are present iterative o clipping is performed to reject outliers The number of samples used at each pixel and the total integration time are retained Source Identification The source identification step is used for excluding sources when the background in the images at each pattern posi
320. referred way to do this would be to multiply all the a coefficients in the expression above by the square root of the pixel scale ratio V Sy Sy and the b coefficients by the reciprocal value V Sy Sx using the scale ratios given above This will correct all pixels to square geometry preserving the area of a pixel located at array center This is the approach used in the distortion coefficients used by the drizzle algorithm see section 5 4 4 Cox et al also solve for the detector y axis orientation relative to the telescope V3 axis finding it to be 44 542 0 006 45 459 0 002 and 45 037 0 005 degrees for Cameras 1 2 and 3 respectively Drizzling One way to apply the geometric distortion correction when combining dithered NICMOS images is to use the drizzle software which is incorporated into the package stsdas analysis dither This software was written to allow geometric distortion corrections to be applied during drizzling In order to do so it is necessary to specify a coefficient file with the parameter drizzle coeffs Geometric distortion coefficient files in a format suitable for use with drizzle are available from the STScI NICMOS web pages and are also provided with the stsdas analysis dither package In these the coefficients from Cox et al have been multiplied by the square root of the pixel scale ratio so that the output images will have square pixels with uniform X and Y scales as described above The absolute pi
321. reprocessing is your only option The basic steps in recalibrating a dataset on your own computer are 1 Assemble any necessary reference files or tables and your raw data files 2 Set the desired calibration switches and reference file name keywords in the primary header of your raw _raw fits data file These determine which steps will be executed by the calibration software and which reference files will be used to calibrate the data Recalibration W NICMOS 3 25 3 Run the calibration software Assembling the Input Files In order to recalibrate your data you need to retrieve all of the reference files and tables that are used by the calibration steps you want to perform The source of these files is the Calibration Database CDBS at STScI A complete description of how to retrieve the reference files is given in chapter 1 of the HST Introduction Setting the Calibration Parameters The calibration software is completely data driven meaning that the calibration steps to be carried out are determined by the values of the calibration switches and the calibration reference files keywords contained in the primary header of the file to be processed An important step is then to set the calibration switches and reference file keywords in the primary header of your raw data file _raw fits to reflect how you want the data recalibrated and which reference files you want to use at each step in the process This is done most easily with
322. rget object The above equation reduces to a set of three equations with three unknowns The solution results in the Stokes parameters for the incoming light For NICMOS the transmission coefficients are Ae i B aay Ses ea k Al Es k p i COS Pps k E Pk where is the position angle of the kth polarizer relative to the NICMOS entrance aperture t is the fraction of light transmitted for a 100 polarized input aligned with the polarizer s axis and l is the fraction transmitted when the incoming light is perpendicular to the axis of the polarizer For NICMOS the observed signal from a polarized source of total intensity I contains an added term in the transmission coefficients namely 0 5 1 I Table 5 9 below presents the properties of the individual polarizers 8 Polarizer efficiency is defined as S 4 Sperp Spar Sperp Where Spar and Sperp are the respective measured signals for a polarizer oriented parallel and perpendic ular to the axis of a fully polarized beam 9 For further detailed information on the derivation of the coefficient matrices see Hines D C Imaging Polarimetry with NICMOS VLT Conference 1998 Analysis of Polarization Images HJ NICMOS 5 45 Table 5 9 NIC1 amp NIC2 Polarizer Properties NIC 1 NIC 2 Filter Pk k tk Ik Filter Pk k tk Ik POLOS 142 0 9717 0 7760 0 0144 POLOL 884 0 7313 0 8981 0 1552 POL120S 116 30 0 4771 0 5946 0 3540 POLI20L 13142 0 6288 0 85
323. ribed INTRO 3 25 N naming conventions files HST data INTRO 2 1 nfitld task INTRO 3 34 ngaussfit task INTRO 3 34 NICMOS absolute photometry NICMOS 5 17 ACCUM mode NICMOS 1 5 association table NICMOS 2 9 bad pixel NICMOS 3 9 BRIGHTOBJ mode NICMOS 1 6 calibration NICMOS 3 1 calibration process NICMOS 3 24 described NICMOS 1 2 emission line filters NICMOS 5 17 file names NICMOS 2 1 grism spectroscopy NICMOS 3 4 grism absolute spectrophotometry NIC MOS 5 18 imset STSDAS tasks INTRO 3 14 keywords NICMOS 2 10 MULTIACCUM mode NICMOS 1 5 paper products NICMOS 2 22 pipeline calibration NICMOS 3 1 PSF NICMOS 5 14 Index HZ NICMOS 5 PSF subtracting NICMOS 5 23 RAMP mode NICMOS 1 6 readout mode NICMOS 1 4 recalibrating data NICMOS 3 23 red leak NICMOS 5 16 NICMOSlook program grism spectroscopy NICMOS 3 4 noise calculation NICMOS NICMOS 3 10 O observation log files APP B 3 Observation Monitoring System APP C 1 observer comment file described APP B 4 OCX file observer comments APP B 4 OMS observation log files APP B 3 OPUS see pipeline P package IRAF concept APP A 5 STSDAS structure INTRO 3 2 INTRO 3 3 paper products NICMOS NICMOS 2 22 parameter data types APP A 10 see also eparam and Iparam setting IRAF APP A 9 PDQ file described APP B 4 Phase II see proposal photometric correction NICMOS
324. rimary pattern type Primary pattern shape Primary pattern purpose Number of points in primary pattern Point spacing for primary pattern arc sec Line spacing for primary pattern arc sec Angle between sides of parallelogram pattern deg Coordinate frame of primary pattern POS TARG or CELESTIAL Orientation of pattern to coordinate frame deg Center pattern relative to pointing yes no Pattern offset method SAM or FOM Position number of this point in the pattern Pattern type Association Keywords Association rootname Name of the association table Role of the dataset in the association e g target first background second background etc allowed val ues EXP_TARG EXP_BCKn PROD_TARG PROD_BCKn where EXP input exposure PROD out put product TARG target BCK background n 1 8 In the SCI image extensions additional keywords describing the data quality are present They give the number of pixels which have a flag different from zero in the DQ extension and a suite of statistical information mean standard deviation minimum and maximum of good pixels in the entire detector and per quadrant on the image Table 2 4 lists some of the relevant keywords that are specific to image extensions they appear in the extension headers but not in the primary header Header Keywords W NICMOS 2 15 Table 2 4 Image Extension Header Keywords in Science Data Files Keyword Name EXTNAME EXTVER INHERIT DATAMIN DATAMAX BUN
325. roduced for an associated set of observations Trailer File _tr1 This FITS ASCII table contains a log of the pipeline calibration processing that was performed on individual datasets and mosaic products Processing Data Quality File _pdq This FITS ASCII table provides quality information on the obser vation mostly on pointing and guide star lock Possible problems encountered e g a loss of guide star lock or a guide star acquisi tion failure are reported here 2 1 2 Science Data Files The raw fits cal fits ima fits and mos fits files are all defined as science data files as they contain the images of interest for scientific analysis File Contents and Organization The data for an individual NICMOS science readout consist of five arrays each stored as a separate image extension in the FITS file The five data arrays represent The science SCI image from the detector An error ERR array containing an estimate of the statistical uncer tainties in units of 10 of the science data An array of bit encoded data quality DQ flags representing known status or problem conditions of the science data NICMOS 2 4 Chapter 2 Data Structures e An array containing the number of data samples SAMP that were used to compute each science image pixel value e An array containing the effective integration time TIME for each science image pixel A grouping of the five data arrays for one science image
326. roid of the target in the NIC2 field of view For comparison with the FSW positions of the target the centroid values need to be converted into detector coordinates by subtracting them from 256 5 For example Star NXCENTER 256 5 133 725 122 775 NYCENTER 256 5 175 708 80 792 In this example the target position we have measured agrees quite well with that determined by the FSW The slight differences are most probably due to the different algorithms used to determine the centroids Recalibrating Coronagraphic Images The user may wish to recalibrate coronagraphic data using the best reference files currently available see section 3 5 Unfortunately at this time there are no standard dark reference files available from the calibration database for ACCUM and BRIGHTOBJ mode observations see section 4 1 3 for a discussion Some coronagraphic observers obtained their own on orbit ACCUM mode darks which are available from the HST Archive and can be used for calibrating the science data If you have questions about calibrating coronagraphic ACCUM images please contact the STScI help desk help stsci edu Any given on orbit flatfield observation with NIC2 will include the coronagraphic hole Because the hole moved with time it is unlikely that NICMOS 5 36 Jf Chapter 5 Data Analysis the hole will be in the same location for a given observation as it was in a flatfield taken at a different time This can have particul
327. rom one readout to the next with the last readout containing the accumulated counts from the entire integration time of the observation In an exposure the number of readouts after the zeroth and the temporal spacing between each read is selected by the user from a set of 16 pre defined sequences The sequence chosen by the user is stored in the value of the SAMP_SEQ keyword in the science data files The user specifies the number of readouts through the NSAMP keyword during the Phase II proposal process NSAMP 1 including the zeroth read images will be returned to the ground For NICMOS the maximum value of NSAMP is 25 in each sequence for a total of 26 images returned to the ground Because MULTIACCUM gives information not only at the beginning and at the end of an exposure but also at intermediate times it is the mode of choice for the vast majority of astronomical observations from objects with large dynamical range to deep field integrations The intermediate reads can also be used to remove the effects of cosmic ray hits and of saturated pixels from the final processed image The images returned to the ground by the MULTIACCUM readout are raw detector readouts since not even the bias level the zeroth read is subtracted This operation is performed by the ground calibration pipeline ACCUM ACCUM is a simplified version of MULTIACCUM the zeroth read is followed by one read the final readout after an amount of time specifi
328. rompt is located Move the cursor to any location in the graphics window Press E to write the plot to the graphics buffer Type q to exit graphics mode a Aa U N At the cl prompt type gf lush Displaying HST Spectra IJ INTRO 3 23 Plots will be printed on the printer defined by the IRAF environment variable stdplot Type show stdplot to see the current default printer use set stdplot printer_name to set the default printer The PostScript kernel psikern allows you to create PostScript files of your IRAF STSDAS plots For example setting the device parameter in a plotting task equal to psi_ port or psi_land invokes psikern and directs your plot to either a portrait mode or a landscape mode PostScript file For example st gt fwplot y3b10104t clh 19 device psi_land st gt gflush tmp pskxxxx The above commands would write a plot of flux vs wavelength in landscape mode into a temporary PostScript file named tmp pskxxxx by a UNIX system See the online help for more about psikern including plotting in color and incorporating PostScript fonts into your plots igi As your plotting needs grow more sophisticated and especially as you try preparing presentations or publication quality plots you should investigate the Interactive Graphics Interpreter or igi This task in the STSDAS stplot package can be used with images as well as two and three dimensional tables and can draw axes error bars labels
329. rot section 4 5 1 Erratic middle column row section 4 5 2 Coronagraphic hole masking section 4 5 3 Vignetting section 4 5 4 e Effects from bright targets Photon induced persistence section 4 6 1 Post SAA cosmic ray persistence section 4 6 2 The Mr Staypuft Effect amplifier ringing section 4 6 3 Optical ghosts section 4 6 4 e Cosmic rays of unusual size section 4 7 e Scattered earthlight section 4 8 4 1 NICMOS Dark Current and Bias Some of the major challenges for achieving high quality NICMOS data reduction arise from difficulties in removing additive components of the instrumental signature that are present in a raw NICMOS image For the purpose of discussion here we will divide these additive components into two categories bias and dark according to whether or not the signal is noiseless and purely electronic in origin bias or noisy and arising from thermal or luminous sources dark In practice the NICMOS bias and dark signals each consist of several different components which exhibit a range of different behaviors In the standard reference files used for processing NICMOS data dark and bias components are combined together as a single DARK image and are handled in the same step DARKCORR of the calnica pipeline processing NICMOS dark images really dark bias are highly dependent on the readout history of the array since it was last reset and therefore cannot be simply rescal
330. s The similar tximage task can be used to generate single group GEIS files from STIS data which can then be used as input to tasks such as resample tt gt tximage data fits 1 c WAVELENGTH r row 4 wave hhh tt gt tximage data fits 1 c FLUX r row 4 flux hhh General Tasks for Spectra IRAF has many tasks for analyzing both one and two dimensional spectral data Many observers will already be familiar with noao onedspec and noao twodspec packages and those who are not should consult the online help Table 3 5 lists some of the more commonly used IRAF STSDAS spectral analysis tasks and below we briefly describe splot one of the most versatile and useful Remember that many of these tasks expect to find WCS wavelength information in the header so you should first run mkmultispec or tomultispec on your data if necessary Analyzing HST Spectra W INTRO 3 31 Table 3 5 Tasks for Working with Spectra Task Package Input Format Purpose boxcar images imfilter Image Boxcar smooth a list of images bplot noao onedspec Multispec image Plot spectra non interactively continuum noao onedspec Image Continuum normalize spectra fitprofs noao onedspec Image Non interactive Gaussian profile fitting to features in spectra and image lines gcopy stsdas toolbox imgtools GEIS image Copy multigroup images grlist stsdas graphics stplot GEIS image List file names for all groups in a GEIS image used to make lists for tasks that do no
331. s are in hand If you need precise relative astrometry you should use an instrument specific task that accounts for image distortion such as the metric task for WF PC 1 and WFPC2 images Analyzing HST Images W INTRO 3 11 Do not use tasks like rimcursor or xy2rd directly on WF PC 1 or WFPC2 images if you require accurate relative positions WF PC 1 and WFPC2 pipelines do not correct for geometric distortions which will affect the accuracy of relative positions Both wmosaic and metric found in the stsdas hst_calib wfpc package correct for this distortion Table 3 1 Additional IRAF and STSDAS Astrometry Tasks Task Purpose compass Plot north and east arrows on an image north Display the orientation of an image based on keywords rimcursor Determine RA and Dec of a pixel in an image wescoords Use WCS to convert between IRAF coordinate systems wcslab Produce sky projection grids for images 1 World Coordinate System WCS Type help specwcs at the IRAF prompt for details Improving Astrometric Accuracy Differential astrometry measuring a position of one object relative to another in an image is easy and relatively accurate for HST images while absolute astrometry is more difficult owing to uncertainties in the locations of the instrument apertures relative to the Optical Telescope Assembly OTA or V1 axis and the inherent uncertainty in Guide Star positions However if you can determine an accurat
332. s case the extension 0 of the primary header must be explicitly specified cl gt hedit n0g70106t_raw fits 0 flatcorr OMIT Do not try to edit a keyword in an extension header unless you are cer tain that the keyword does not reside in the primary header Image sections can be specified in the case of NICMOS data with the same syntax as all IRAF images For example to specify a pixel range from 101 to 200 in the x direction and all pixels denoted by an asterisk in the y direction from the second error image in a file the complete file name specification would be n0g70106t_cal fits err 2 101 200 If you use both extension and image section syntax together the exten sion name or number must come first enclosed in one set of brackets and the image section specification in a second set of brackets NICMOS 2 20 Chapter 2 Data Structures 2 4 From the Phase II Proposal to Your Data The connection between the Exposure Logsheet that each observer fills out during the Phase II proposal process and the datasets and associations that the observer receives once the observations are executed can be better understood through some examples The first example shows an exposure logsheet entry that will generate only one dataset Exposure Number 1 Target Name HDF Config NIC2 Opmode MULTIACCUM Aperture NIC2 Sp_Element F160W Optional Parameters SAMP SEQ STEP256 NSAMP 12 NUMBER_of Iter
333. s cosmic rays from MULTIACCUM observations and the STIS pipeline automatically removes cosmic rays from CR SPLIT association products Displaying HST Images W INTRO 3 5 3 2 1 The display Task The most general IRAF task for displaying image data is the display task the best choice for a first look at HST imaging data To display an image you need to 1 Start an image display server such as SAOimage in a separate win dow from your IRAF session either from a different xterm window or as a background job before starting IRAF To start SAOimage type the following saoimage amp 2 Load the images tv package from the window where you re running IRAF cl gt images im gt tv Several different display servers including SAOimage ds9 the next generation of SAOimage and Ximtool can be used with IRAF ds9 Y may be retrieved from http hea www harvard ed u RD ds9 Ximtool may be retrieved from ftp iraf noao edu iraf x1 liraf 3 Display the image with the IRAF display task using the syntax appropriate for the file format Chapter 2 explains how to specify GEIS groups and FITS extensions tv gt display fname cOh 2 1 GEIS group 2 tv gt display fname fits 11 1 FITS extension 11 tv gt display fname fits sci 3 1 FITS extension sci 3 Note that when using display or any other task on GEIS images you do not need to specify a group the first group is the default However w
334. s created with x and y dimensions large enough to encompass the maximum offsets in each direction 3 Pixel values in the mosaic image are populated by combining sam ples from overlapping images The individual images are aligned using bilinear interpolation and the value at a given mosaic pixel location is computed from the error weighted mean of the samples at that location Samples flagged as bad are excluded and if three or more samples are present iterative sigma clipping is used to reject remaining outliers The number of samples retained for a given pixel and their total integration time is recorded in the SAMP and TIME images respectively If all samples are rejected for a pixel the mosaic image SCI ERR SAMP and TIME values are set to zero and a combination of all DQ flags is retained Recalibration W NICMOS 3 23 3 5 Recalibration 3 5 1 This section is intended to help you decide whether your data were calibrated with optimal calibration reference files and to help you decide whether you need to recalibrate your data Why Recalibrate In some cases NICMOS calibrated data produced by the OPUS pipeline the standard calibration are adequate for scientific applications However as with all instruments there is often room for improvement and you may find it worthwhile or even necessary to reprocess your data perhaps following additional procedures which are not part of the standard pipeline As described at the start
335. s the effect of edge enhancement One way to suppress high frequency variations in the images is to convolve one or both by a Gaussian filter This may help reduce residuals in the subtracted image The IRAF task gauss may be used to smooth the images The resulting images for two different convolutions with o 0 4 and o 0 8 are presented in figure 5 9 Figure 5 9 PSF Subtraction F110W filter images obtained in back to back orbits with a roll of the spacecraft between orbits Images convolved with a Gaussian function o 0 4 left and o 0 8 right and subtracted orbit 4 5 orbit 4 5 04 6 08 In this example the o 0 4 convolution results in a slight improvement over the subtractions shown in figure 5 8 Possibly this choice is undersmoothing the data The o 0 8 convolution more closely matches the low frequency components Determining a suitable degree of smoothing will require experimentation by the user Analysis of Polarization Images W NICMOS 5 43 5 7 Analysis of Polarization Images 5 7 1 Introduction The filter wheels of cameras NIC1 and NIC2 each contain three polarizing filters with unique polarizing efficiencies and position angle offsets The original design specified that the position angle of the primary axis of each polarizer as projected onto the detector be offset by 120 from its neighbor and that the polarizers have identical efficiencies While this clean concept was not strictly achieved
336. s wavelength dependence the flatfielding cannot be performed before the spectra are extracted and wavelength calibrated The corrected flux f A is computed as follows fy fayny A where q x y A are interpolated flatfields For wavelengths where narrow band flatfields are available they are used For other wavelengths the correction factors are derived through interpolation from a set of monochromatic flatfield images see Storrs et al 1999 NICMOS ISR 99 002 The list of flatfields to be used is specified in calnicc setup and users can provide their own preferred flatfields The default list is shown in table 5 10 Table 5 10 Default Flatfields For Spectra Flatfield File Ax u FWHM u Filter i191346kn_flt fits 1 07990 0 0096000 F108N i191346mn _fit fits 1 12830 0 0110000 F113N i191346pn_flt fits 1 64600 0 0170000 F164N i191346qn_flt fits 1 65820 0 0164000 F166N i191346sn_flt fits 1 87380 0 0192000 F187N i191346tn_fit fits 1 90030 0 0174000 F190N i1913470n_flt fits 1 96390 0 0186000 F196N i1913471n_fitfits 1 99740 0 0206000 F200N i1913472n_flt fits 2 12130 0 0206000 F212N i1913473n_flt fits 2 14870 0 0200000 F215N i1913475n_fitfits 2 39770 0 1975000 F240M Flux calibration and Correction for Pixel Response Function Once the spectra are extracted the count rates in ADU second are converted to physical units using calibration data form photometric standards P330E and G191B2B Undersampling of NICMOS grism i
337. sion header keywords This feature circumvents the large scale duplication of keywords that share the same value for all extensions The primary header keywords effectively become global keywords for all image extensions The FITS standard does not cover or imply keyword inheritance and while the idea itself is simple its consequences are often complex and sometimes surprising to users Generally keyword inheritance is the default and IRAF STSDAS applications will join the primary and extension headers and treat them as one For example using imheader as follows on a FITS file will print both primary and extension header keywords to the screen cl gt imheader fitsfile fits sci 2 long page Using imcopy on such an extension will combine the primary and extension headers in the output HDU even if the output is going to an extension of another FITS file Once IRAF has performed the act of inheriting the primary header keywords it will normally turn the inheritance feature off in any output file it creates unless specifically told to do otherwise If you need to change the value of one of the global keywords inherited from the primary header you must edit the primary header itself i e extension 0 INTRO 2 8 W Chapter 2 HST File Formats Keyword inheritance is not always desirable For example if you use imcopy to copy all the extensions of a FITS file to a separate output file IRAF will write primary header keyw
338. sion of the image using the Java Image Preview Application JIPA tool that is part of StarView For spectra a simple GIF image of the calibrated spectrum will be displayed JIPA and VTT can also display an image s FITS header under the JIPA Tools menu The JIPA preview of the WFPC2 image U2900103T retrieved in the previous search for WFPC2 images of M87 is shown in figure 1 2 along with the window displaying part of the FITS header file of this image Other display options with StarView include DSS which will display a 20 x 20 Digital Sky Survey image at the target coordinates while the Overlay button will display the same DSS image with outlines of the HST instrument apertures at the target coordinates superimposed on it at the orientation of the observation selected The References button provides a link to any known published papers citing the dataset as listed in ADS Note that the HST images displayed by the Preview are of reduced quality compared to the actual data files and cannot be downloaded They are only meant to provide a quick check that the datasets found by the search met the search criteria i e contained the object s of interest and are of the desired quality INTRO 1 8 W Chapter 1 Getting HST Data Figure 1 2 JIPA preview of WFPC2 image U2900103T along with image header file using Preview option yi JIFA YI jbD KOOLNAME UZIUUIUSI File Tools Help Target M8 Instr WFPCZ Filtl FS
339. slightly different way The values given here are the scale ratios derived from the geometric distortion solution described in section 5 4 3 and formally apply to the aspect ratio of the pixels at array center position 128 128 These are the appropri ate values to use in combination with the geometric distortion corrections The X and Y scales reported by the NICMOS History Tool are in effect mean values over the array averaging over the scale changes induced by geometric distortion Astrometry Pixel scales and Geometric Distortion J NICMOS 5 21 was also moved to substantially reduce the vignetting Cox et al have derived an improved Camera 3 distortion solution which has not been presented in any other NICMOS document but which we describe here For Camera 3 these values therefore supersede those from the original ISR by Cox et al The maximum total positional deviations in pixels assuming zero distortion at field center are approximately 0 9 0 25 and 0 75 pixels for Cameras 1 2 and 3 respectively Cox et al found that quadratic relations were adequate for describing the distortion given the accuracy of the observational measurements Given a pixel position x y we define new coordinates x y relative to the array center here chosen to be at pixel 128 128 x x 128 y y 128 The positions corrected for distortion x y are then given by Xc ajo X aj y a20x ap xy ayn y Yo
340. software implementing WARNCALC will be reported in the Space Telescope Analysis Newsletter STAN and posted on the NICMOS website 3 4 Mosaicing calnicb Observing strategies with NICMOS vary according to the nature of the target object and of the wavelength chosen for the observation Extended objects may require mosaicing Long wavelength observations will need chopping onto the sky to remove the telescope thermal background from the target frame Multiple repetitions of the same exposure may be requested to improve cosmic ray removal to control statistical fluctuations and to increase the signal to noise on one target while avoiding saturation on another Dither mosaicing and chop patterns of exposures are specified at the Phase II proposal level via the optional PATTERN parameter multiple exposures at the same pointing are specified in Phase II by setting the Number_of_iterations to a value greater than one All these options which can also be set simultaneously create an association of datasets see the discussion of Associations in appendix B The calnicb task produces the combined or mosaiced image from the multiple images contained in a NICMOS association The task also performs background subtraction and source identification on the images in the association It should be noted that calnicb is not the only method available for creating mosaics from multiple NICMOS images nor is it necessarily ideal for all applications
341. ss and parameters use calnicc The NICMOSlook user manual written by W Freudling R Thomas and L Yan the software and instructions for its installation can be found on the ST ECF NICMOSLOOK web site Because NICMOS grism data processing and extraction are not really pipeline procedures this handbook will defer an overview of grism reduction methodology and the software tools calnice and NICMOSlook until chapter 5 where the discussion of NICMOS Data Analysis is presented You cannot run either calnicc or NICMOSlook unless you have an IDL licence Basic Data Reduction calnica IJ NICMOS 3 5 3 3 Basic Data Reduction calnica The calnica task operates on individual NICMOS datasets and performs the job of removing the instrumental signature from the raw science data The calnica task also tries to identify cosmic ray hits and combines the multiple readouts in MULTIACCUM observations The inputs to calnica are the raw science _raw fits files The output of calnica is usually a single file containing the calibrated science data _cal fits For MULTIACCUM mode datasets there is an additional intermediate output file _ima fits which contains the calibrated data from all the intermediate readouts The _ima fits data are fully calibrated up to but not including the cosmic ray rejection The format of the input and output science data files are identical so that the output data can be reused as input to calnica if des
342. star keywords identify the stars that were scheduled to be used and in the event of an acquisition failure may not be Appendix C Using Observation Logs IJ APP C 11 the stars that were actually used The following list of cmh keywords is an example of two star guiding GSD ID 0853601369 1 Dominant Guide Star ID GSD RA 102 42595 Dominant Guide Star RA deg GSD_DEC 53 41362 Dominant Guide Star DEC deg GSD_MAG 11 251 Dominant Guide Star Magnitude GSR_ID 0853602072 Roll Guide Star ID GSR_RA 102 10903 Roll Guide Star RA deg GSR_DEC 53 77683 Roll Guide Star DEC deg GSR_MAG 12 426 Roll Guide Star Magnitude If you suspect that a target has rolled out of the aperture during an exposure you can quickly check the counts in each group of the raw science data As an example the following IRAF commands can be used to determine the counts in each group cl gt grlist z2204040dt d0h 1 24 gt groups lis cl gt imstat groups lis Some observations can span several orbits If during a multiple orbit observation the guide star reacquisition fails the observation may be terminated with possible loss of observing time or switch to other less desirable guiding modes The GSACQ keyword in the cmh header will state the time of the last successful guide star acquisition GSACQ 136 14 10 37 43 Actual time of GS Acquisition Completion C 3 2 Guide Star Acquisiti
343. t acquisition moving target APP C 12 task IRAF concept APP A 6 tomultipsec task extract STIS spectral orders INTRO 3 27 trailer file described APP B 4 NICMOS NICMOS 2 3 NICMOS 2 10 transformation pixel coordinates to RA and Dec INTRO 3 10 ttools package STSDAS tables INTRO 3 4 txtable task extract arrays INTRO 3 29 U unit counts to flux mag conversion INTRO 3 18 units conversion NICMOS NICMOS 5 6 user support help desk 1 1 ii V variable IRAF environment APP A 11 W waiver FITS format INTRO 2 17 wavelength calibration NICMOS grism NICMOS 5 51 combine with flux mkmultispec INTRO 3 25 NICMOS 8 Index World Coordinate System mkmultispec task INTRO 3 25 world wide web software obtaining APP A 15 X xy2rd task pixel coordinates to RA and Dec INTRO 3 10 Z zeroth read non zero NICMOS NICMOS 5 16 zeroth read subtraction NICMOS NICMOS 3 9
344. t shorter effective exposure time The actual exposure time used per pixel can be determined by looking at the TIME 1 array of the final calibrated image NICMOS 4 42 Chapter 4 Anomalies and Error Sources CHAPTER 5 Data Analysis In this chapter 5 1 STSDAS Software 5 1 5 2 The NICMOS History Tool 5 5 5 3 Photometric Calibrations 5 6 5 4 Astrometry Pixel scales and Geometric Distortion 5 19 5 5 PSF Subtraction 5 23 5 6 Coronagraphic Reductions 5 29 5 7 Analysis of Polarization Images 5 43 5 8 Grism Data Reduction 5 47 This chapter describes specific tools and topics related to the analysis of NICMOS data The first section points out some STSDAS tools for analyzing NICMOS images The tools described here are specialized for use with NICMOS and supplement the more general STSDAS tasks described in chapter 3 of the HST Introduction The remainder of the chapter deals with topics of more or less general interest photometric calibration PSF subtraction coronagraphic reductions polarimetric analysis and grism data reduction 5 1 STSDAS Software Software tools for NICMOS FITS files available in the STSDAS packages toolbox imgtools mstools and hst_calibnicmos have been designed to maintain compatibility with pre existing analysis software The tools have either been written in ANSI C or are IRAF CL scripts interfacing with pre existing IRAF STSDAS tasks Some of the new tools accept a varie
345. t task plot echelle spectra INTRO 3 22 emission line filters NICMOS NICMOS 5 17 engineering data OMS logs APP C 1 environment variable IRAF APP A 11 eparam task editing parameters APP A 9 exposure log sheet NICMOS NICMOS 2 20 exposures multiple NICMOS combining NICMOS 3 20 extension FITS file INTRO 2 3 FITS appending INTRO 2 8 F file PostScript creating INTRO 3 23 files data formats APP A 13 data quality PDQ APP B 4 FITS working with INTRO 2 5 naming conventions INTRO 2 1 naming conventions NICMOS NIC MOS 2 1 observation log APP B 3 observer comments OCX APP B 4 rootname APP B 3 specifying STIS INTRO 3 21 trailer APP B 4 filters NICMOS available NICMOS 1 3 FINE LOCK guidance APP C 10 FITS files working with INTRO 2 3 INTRO 2 12 format described INTRO 2 3 GEIS files in INTRO 2 13 table INTRO 2 9 table array in cell INTRO 2 11 waiver INTRO 2 17 fitting package fit spectra INTRO 3 34 tasks in INTRO 3 34 flatfield NICMOS NICMOS 3 14 flux combine with wavelength mkmultispec INTRO 3 25 from counts INTRO 3 18 format IRAF and STSDAS files APP A 13 FOS display spectra INTRO 3 20 fwplot task spectra display INTRO 3 20 Index HZ NICMOS 3 G GEIS format described APP A 13 header file INTRO 2 15 working with INTRO 2 15 geometric distortion correction INTRO 3 10 GHRS display spectra INTRO 3 20 grism
346. t to 0 0 Because calnica v3 3 was released after the end of NICMOS Cycle 7 operations all Cycle 7 and 7N data retrieved from the HST archive prior to 26 September 2001 were pro cessed by OPUS using the older non linearity corrections If you think that your data may benefit from the newer more accurate linearity cor rections you should reprocess the images see section 3 5 or retrieve them again using OTFR which will automatically process them using the new nonlinearity corrections 1 The correction term in the nonlinearity equation given above is quadratic This is then multiplied by the uncorrected flux yielding an effectively cubic rela tion between uncorrected and corrected values BARSCORR Bars Correction Some NICMOS images will have pairs of bright and dark columns or rows which have come to be known as bars The bars are believed to NICMOS 3 14 JJ Chapter 3 Calibration arise from electrical cross talk in the detector lines during the readout of one camera when another of the cameras enters the auto flush idle state The bars manifest themselves as a noiseless DC offset of a few DNs along a pair of columns or rows with the pattern replicated exactly in all four image quadrants They are discussed and illustrated in section 4 2 of this Handbook Versions 3 3 and higher of calnica use the BARSCORR routine to remove the effects of the bars from MULTIACCUM observations The routine scans pairs of columns or rows de
347. t use group syntax grplot stsdas graphics stplot GEIS image Plot arbitrary lines from 1 D image overplots multiple GEIS groups no error or wavelength information is used grspec stsdas graphics stplot Multispec GEIS image Plot arbitrary lines from 1 D image stack GEIS groups magnify images imgeom Image Interpolate spectrum on finer or coarser pixel scale nfitld stsdas analysis fitting Image table Interactive 1 D non linear curve fitting see section 3 5 4 ngaussfit stsdas analysis fitting Image table Interactive 1 D multiple Gaussian fitting see section 3 5 4 poffsets stsdas hst_calib ctools GEIS image Determine pixel offsets between shifted spectra rapidlook stsdas hst_calib ctools GEIS image Create and display a 2 D image of stacked 1 D images recombine stsdas hst_calib ctools GEIS image Combine sum or average GEIS groups in a 1 D image with option of propagating errors and data quality values resample stsdas hst_calib ctools GEIS image Resample FOS and GHRS data to a linear wavelength scale see section 3 5 1 sarith noao onedspec Multispec image Spectrum arithmetic scombine noao onedspec Multispec image Combine spectra sfit noao onedspec Multispec image Fit spectra with polynomial function sgraph stsdas graphics stplot Image table Plot spectra and image lines allows overplotting of error bars and access to wavelength array see section 3 4 1 specalign stsdas hst_calib ctools GEIS image Align and combine shifted spectra see
348. t visit of a two visit observation set The accompanying science observations would have been obtained during the second visit The ACCUM BRIGHTOBJ and MULTIACCUM observing modes have all been used for acquisitions and for the science observations Each type of data requires different calibration steps and dark reference files Coronagraphic Acquisitions Coronagraphic imaging requires an acquisition sequence at the beginning of the visit to center the target in the coronagraphic hole The size of the coronagraphic hole is smaller than typical HST blind pointing errors The procedure for a coronagraphic acquisition is to first image the target in Camera 2 using blind pointing and then use either an onboard using the NIC2 ACQ aperture reuse target offset or interactive acquisition to acquire the target A telescope slew is calculated and commanded to move the position of the hole over the image of the target During the Second Servicing Mission SM2 Science Mission Orbital Verification SMOV it was determined that decentering a point source by a small amount x 0 75 y 0 25 pixels from the center of the hole reduced the background intensity program ID 7052 see NICMOS IDT report Results from SMOV 7052 NICMOS Coronagraphic Per formance Verification Based on the SMOV results this offset was implemented in the NICMOS ACQ flight software for use in Cycle 7 science observations The target is positioned on the NIC2 CORON ap
349. ta from all readouts into a single image In MULTIACCUM mode the data from all readouts are analyzed pixel by pixel iteratively computing a linear fit to the accumulating counts versus exposure time relation and rejecting outliers from the fit as CR hits The default rejection threshold is set to 40 but the user can override this if desired by setting the crthresh task parameter for calnica The fit for each pixel is iterated until no new samples are rejected Pixel samples identified as containing a CR hit are flagged in the DQ images of the intermediate MULTIACCUM _ima fits file with a DQ value of 512 The pixel values in the SCI and ERR images of the _ ima file however are left unchanged Once all outliers have been identified a final countrate value and its uncertainty are computed for each pixel using only non flagged samples The result of this operation is stored as a single imset in the output cal fits file in which the number of unflagged samples used to compute the final value for each pixel and the total exposure time of those samples is reflected in the SAMP and TIME images respectively The variance ascribed to the final mean countrate is the uncertainty in the slope of the counts versus time relation at each pixel location and is recorded in the ERR image of the _cal fits file Pixels for which there are no unflagged samples e g permanently hot or cold pixels will have their output SCI ERR SAMP and TIME values set
350. tains a complete HST FITS header keyword dictionary with descriptions of the keywords used by NICMOS and other HST instruments Table 2 3 Science Data File Primary Header Keywords Keyword Name NEXTEND DATE FILENAME FILETYPE TELESCOP INSTRUME EQUINOX ROOTNAME IMAGETYP PRIMESI TARGNAME RA_TARG DEC_TARG PROPOSID LINENUM PR_INV_L PR_INV_F PR_INV_M ORIENTAT SUNANGLE MOONANGL FGSLOCK DATE OBS TIME OBS EXPSTART EXPEND EXPTIME EXPEND CAMERA Meaning Image Keywords Number of extensions in the file up to 130 for MULTIACCUM Date on which the file was generated Name of the file Type of data SCI Science Data File SPT Support File ASN_TABLE Association Table HST Instrument used NICMOS Equinox of the celestial coordinate system J2000 0 for HST observations Data Description Keywords Rootname IPPPSSOOT of the dataset Image type EXT external image FLAT flatfield image DARK dark image Primary Instrument used for the observation Target Information Proposer s target name Right Ascension of the target degrees J2000 Declination of the target degrees J2000 Proposal Information Proposal s identification number Exposure s logsheet line number from the Phase 2 proposal Principle investigator last name Principle investigator first name Principle investigator middle initial Exposure Information Position angle of the image y axis degrees East of North Angle between sun and V1 a
351. tarting an IRAF session For UNIX environments this is done with setenv nref path and setenv ntab path where you should specify the path to your reference file directory Do not forget the trail ing slash Running the Calibration Software After you change the header keyword values for your raw data files you are ready to recalibrate your data To run calnica type the name of the task followed by the names of the input raw data file and desired output calibrated data file For example to recalibrate the dataset n0g70106t you could type ni gt calnica n0g70106t_raw fits n0g70106t_cal fits Recalibration W NICMOS 3 27 or simply ni gt calnica n0g70106t To run calnicb the name of the association table must be given as input ni gt calnicb assoc_id_asn To run calnicb on a subset of the _cal fits files it is sufficient to edit the _asn fits table and remove the undesired files The calibration routines calnica and calnicb will not overwrite an existing output file If the calibration tasks are run in the directory where the original calibrated files are located a different output file name must be specified There are some calnicb processing parameters which reside in the association _asnfits 1 table header and not in any FITS file image header and which therefore cannot be changed using chcalpar or hedit In particular to change the ILLMCORR and ILLMFILE parameters y
352. ter 5 Data Analysis ee Appendixes Hi Part Ill Appendixes APPENDIX A IRAF Primer In this appendix A 1 Initiating IRAF A 2 A 2 IRAF Basics A 4 A 3 Getting IRAF and STSDAS A 15 The Image Reduction and Analysis Facility IRAF developed by the National Optical Astronomy Observatories NOAO forms the basis of the Space Telescope Science Data Analysis System STSDAS IRAF contains numerous packages of programs called tasks that perform a wide range of functions from reading data tapes to producing plots and images Most astronomers will already be familiar with IRAF but we provide this tutorial for HST observers who are beginners with IRAF It includes information on How to set up IRAF the first time you use the software e How to start and stop an IRAF session e Basic concepts such as loading packages setting parameters etc e How to use the on line help facility Additional information on IRAF in particular A Beginner s Guide to Using IRAF is available through the NOAO IRAF Home Page at http iraf noao edu APP A 1 APP A 2 I Appendix A Initiating IRAF A 1 Initiating IRAF This section explains How to set up your IRAF working environment e How to start and logout of the IRAF program We assume that your site has IRAF and STSDAS installed If not you a must obtain and install the software See appendix section A 3 for details A 1 1 Setting Up IRAF Before running
353. that applies to the observation as a whole i e to all the groups in the image and the group specific keyword information is stored in the group parameter block of each data group in the binary data file The number of groups produced by a given observation depends upon the instrument configuration the observing mode and the observing parameters Table 2 2 lists the contents and the number of groups in the final calibrated image for the most commonly used modes of each instrument which uses the GEIS data format Table 2 2 Groups in Calibrated Images by Instrument and Mode Number Instrument Mode of Description Groups FGS All 7 FGS data are not reduced with IRAF and STSDAS Therefore FGS groups have different meaning than for the other instruments FOC All 1 All FOC images have only a single group FOS ACCUM n Group n contains accumulated counts from groups subintegrations 1 2 n The last group is the full exposure RAPID n Each group is an independent subintegration with exposure time given by group parameter EXPOSURE GEIS File Format HJ INTRO 2 15 Number Instrument Mode of Description Groups HSP All 1 HSP datasets always have only a single group that rep resents either digital star dOh cOh digital sky d1h c1h analog star d2h c2h or analog sky d3h c3h GHRS ACCUM n Each group is an independent subintegration with exposure time given by group parameter EXPOSURE If
354. the STSDAS toolbox headers package to look at the headers of the science data The output from iminfo summarizes on one screen the relevant information about an observation table 2 7 and the instrument configuration during the observations table 2 8 by reading and reporting the values of various keywords Working with NICMOS Files IJ NICMOS 2 17 Table 2 7 Observation Information in iminfo Listing Field Descriptor Header Keyword Source Rootname ROOTNAME Instrument INSTRUME Target Name TARGNAME Program Observation set ROOTNAME positions 2 4 ROOTNAME positions 5 6 Observation ROOTNAME positions 7 8 File Type FILETYPE Obs Date DATE OBS or FPKTTIME Proposal ID PROPOSID Exposure ID PEP_EXPO Right Ascension CRVAL1 Declination CRVAL2 Equinox EQUINOX Table 2 8 NICMOS Specific Information in iminfo Listing Field Descriptor Image type Number of extensions Camera number Aperture Filter name Observation Mode Number of initial final reads Number of intermediate samples MULTIACCUM sequence Exposure time sec Readout speed Association ID Number of Iterations Calibration steps done Header Keyword Source IMAGETYP NEXTEND CAMERA APERTURE FILTER OBSMODE NREAD ACCUM NSAMP MULTIACCUM SAMP_SEQ EXPTIME READOUT ASN_ID NUMITER Switches whose values are set to PERFORMED Switches are ZSIGDONE ZOFFDONE MASKDONE BIASDONE NOISDONE DARKDONE NLINDONE BA
355. three weeks long were undertaken one from 12 January through 1 February 1998 and the second from 4 June through 28 June 1998 During these periods the HST secondary mirror was moved in order to bring Camera 3 into the range where its correct focus could be reached by the PAM The focus history of the telescope at the time of your observation can be determined using the NICMOS History Tool see section 5 2 In addition the NICMOS PSF varies somewhat as a function of position on the array and this can affect photometry made either with small apertures by changing the effective aperture correction as a function of position or using PSF fitting programs such as daophot unless there are enough stars in the field for the program to derive a positionally dependent Photometric Calibrations I NICMOS 5 15 PSF The focus variations however are relatively small see NICMOS ISR 98 005 NICMOS Focus Field Variations and Focus Centering Suchkov amp Galas 1998 We have used synthetic PSFs from TinyTim see Aperture Correction on page 5 15 to determine the positional dependence of the aperture correction as a function of position on NIC2 where the focus variations are largest For F110W the effect should be largest at short wavelengths the maximum to minimum variation in the aperture correction for photometry measured within a 2 pixel radius is lt 2 The variations are expected to be smaller for the other cameras and for images
356. time intervals Therefore each and every combination of ACCUM exposure time and NREAD requires a unique dark image for calibration and it was not practical to calibrate all of these on orbit In addition as has also been noted the shading particularly for NIC2 also depends on the instrument temperature 4 1 4 4 1 5 NICMOS Dark Current and Bias IJ NICMOS 4 13 At the present time there are no standard DARK calibration reference files available from the HST Calibration Database for use with ACCUM mode data The DARK reference files used for processing ACCUM mode images in the OPUS pipeline were dummies In principle it should be possible to create synthetic ACCUM dark reference files using a procedure similar to that which has been used for MULTIACCUM data In the future STScI may make a tool available for generating synthetic ACCUM mode darks but the analysis needed to do this has not yet been carried out Many individual on orbit ACCUM mode dark exposures are available from the Archive and it is not unlikely that for any given ACCUM mode science exposure there will be darks available with the right exposure time if not necessarily the right temperature If you need to calibrate ACCUM mode science images you should search the Archive to see if suitable darks are available or discuss the matter with your Contact Scientist In general BRIGHTOBJ mode exposures are so short that true linear dark current is negligible Moreover by d
357. tion is estimated The images at each pattern position are searched for pixels suspected to contain signal from a source The median signal level in the image is computed and pixels Mosaicing calnicb J NICMOS 3 21 that are more than 4 50 above the median are considered as candidates Spurious results such as pixels containing cosmic ray hits are filtered out by searching neighboring pixels and only retaining those candidates that have two or more neighbors that are also above the threshold The DQ flag of the source affected pixels is then set to 1024 Background Estimation and Removal The background signal is estimated and removed from the images at each pattern position Two types of background are subtracted from the images 1 A constant background signal level which is estimated from the images themselves 2 In principle a two dimensional residual background may exist due to spatial variations in the thermal emission of the telescope and instru ment Calnicb has a mechanism for removing this by subtracting the ILLMFILE reference image from each image In practice however it does not appear that there are strong spatial illumination variations requiring such corrections and therefore the ILLMFILEs used in the processing pipeline are dummies with no effect on the data values The step may also be turned off entirely by setting ILLMCORR to OMIT in the association table by default it is set to PERFORM even though dummy files
358. tion of Spectra The positions of the direct objects can be used to compute the location and orientation of the spectra The positions of spectra relative to the position of the object on the direct image is parameterized in grismspec dat However the orientation of spectra varies enough from observation to observation so that a tracing of spectra is necessary for accurate spectrum extraction See the NICMOSlook manual for details Background Subtraction After source identification an estimate of the two dimensional background level is derived and removed from each image The grism image is not flat fielded and the QE variations across the NICMOS detectors are strong implying that a significant structure is present in an image of blank sky Several options to subtract this background are provided They include interpolation over the region of the spectra or subtracting scaled versions of background images The extraction software determines the regions of interpolation excluding positions occupied by other spectra in the image The on orbit grism flatfields which are normally not used for grism data processing see Flatfielding below can provide one convenient way to artificially remove the background from spectral images before extracting the spectra This is a particularly useful procedure if your field is crowded and other sources might contaminate the regions on either side of the spectra used to determine the background The grism f
359. tion or for assessing small aperture pointing stability and 2 to display the slew and tracking anomaly flags with the highest resolution Table C 2 lists the table column heading units and a brief definition rootnamej cmi This table contains data that were averaged over three second intervals It includes the same information as the cmj table and also includes orbital data e g latitude longitude limb angle magnetic field values etc and instrument specific items It is best suited for a quick look assessment of pointing stability and for studying trends in telescope or instrument performance with orbital environment Table C 3 lists the table column heading units and a brief definition rootnamej_cmi j h fits The above three GEIS files are actually archived as FITS files They may be worked with as such or run through the STSDAS task strfits to convert them Observation Log File Contents August 1995 version The contents of observation log files created between August 1995 and February 1997 are as follows APP C 4 Appendix C Observation Log Files e rootnamej jih This GEIS header file the analog to the cmh file contains the time interval the rootname averages of the pointing and spacecraft jitter the guiding mode guide star information and alert or failure keywords Figure C 1 shows a representative observation log header file e rootnamej jid This GEIS image a significant enhancement of the old cmj file
360. tion procedures This chapter describes the most common problems affecting NICMOS data at the level of frame by frame processing In some cases recognizing and treating problems with NICMOS data requires a moderately in depth understanding of the details of instrumental behavior problems with dark and bias subtraction are good examples Where appropriate this chapter offers a fairly detailed discussion of the relevant workings of the NICMOS 4 1 NICMOS 4 2 J Chapter 4 Anomalies and Error Sources instrument but the reader should consult the NICMOS Instrument Handbook for further details Each section of this chapter deals with a different aspect of NICMOS data processing roughly following the order of the processing steps in the standard STSDAS pipeline Various potential problems are described and illustrated Each discussion then has a subsection labeled Cures which offers possible solutions to the problems at hand The art of NICMOS data processing is still evolving and new techniques are being developed by users worldwide Some of these have been encoded into software which is now distributed with STSDAS New processing methods and routines are still being developed at STScI and will be provided in the future the reader should consult the STScI NICMOS WWW pages to look for new developments and software tools We begin with a checklist of potential NICMOS instrumental anomalies and potential data processing problems about which the
361. tions T Source of transmission or association product number M Merged real time and tape recorded N Retransmitted merged real time and tape recorded O Retransmitted real time letter O P Retransmitted tape recorded R Real time not recorded T Tape recorded 0 Primary association product number zero 1 8 NICMOS background association product B 2 Suffixes of Files Common to all Instruments The three character suffix of a data file e g dOh identifies the type of data that a file contains Because the meanings of these suffixes change from instrument to instrument please refer to the appropriate instrument specific Data Structures chapter for their definitions Several types of file suffixes are however common to all instruments OMS Files Observatory Monitoring System OMS files having suffixes cm or ji contain Observation Logs describing how the HST spacecraft behaved during a given observation OMS headers which you can read with the IRAF task imheader see section 2 3 3 in the HST Introduction APP B 4 lf Appendix B Suffixes of Files Common to all Instruments are divided into groups of keywords that deal with particular topics such as SPACECRAFT DATA BACKGROUND LIGHT POINTING CONTROL DATA and LINE OF SIGHT JITTER SUMMARY The headers themselves provide short descriptions of each keyword OMS tables and images record spacecraft pointing information as a function of time For more information
362. tive HST instrument WFPC2 STIS NICMOS and ACS are explained in detail in their respective instrument data handbooks However we recommend a careful reading of this handbook before proceeding to the instrument data handbooks and before starting to work on your HST data The present document is an updated version of chapters 1 3 of the HST Data Handbook v 3 0 and is based on the information available as of December 2001 In particular it is written under the assumption that the ACS and NICMOS instruments will be fully functional following HST Servicing Mission 3B SM3B Many changes in the HST Data Archive and HST data reduction software have occurred since v 3 0 of the Hubble Data Handbook These differences are covered in this document and include but are not limited to 1 Expansion of the HST Data Archive into the Multimission Archive at Space Telescope MAST which currently includes 14 satellite mis sion archives as well as ground based survey data 2 The ability to retrieve MAST data using the World Wide Web 3 New capabilities of the StarView program for searching for and retrieving HST and other MAST data 4 The introduction of PyRAF a new Python based alternative to the IRAF cl shell and 5 A new distinction between waiver FITS format used to archive data from the older HST instruments such as WFPC and FOS and the FITS extension format used for the newest instruments STIS NIC MOS and ACS vii viii Hi
363. to amplifier glow as well as the associated Poisson noise from this signal This nominal Poisson noise is propagated into the ERR array of the NICMOS calibrated images by calnica Figure 4 1 Amplifier glow images for NICMOS cameras 1 2 and 3 NIC2 Bias Shading and Pedestal There are three readily identifiable but not necessarily physically distinct components of the NICMOS bias the detector reset level shading and variable quadrant bias or pedestal Bias Reset Level First a net DC bias with a large negative value of order 25000 ADU is introduced when the detector is reset This bias is different in each readout quadrant but is essentially constant within each quadrant In NICMOS 4 6 W Chapter 4 Anomalies and Error Sources standard MULTIACCUM processing this is removed by subtracting the so called zeroth readout of the image from all subsequent readouts e g in the ZOFFCORR step of calnica It is therefore not a component of any calibration reference file but is removed using the zeroth readout of the science image itself Shading Shading is a noiseless signal gradient a pixel dependent bias which changes in the direction of the pixel clocking during a readout This bias change is caused by a temperature dependence of the readout amplifier bias The amplifier temperature changes rapidly during the readout of the array The result is a bias which changes considerably between the time the first and last
364. to change Figure A 6 shows a sample of the epar editor at work invoked by typing epar strfits Figure A 6 Editing Parameters with epar STSDAS Move Through a E a Parameters es Image Reduction and Analysis Facility fitsi Using Arrow Keys TASK strfits fits_fil q mtg FITS data source file_lis 1 999 File list Type New Values e ira fil TRAF filenane gt template fil GOL Raramp ier Seumas no Print FITS header cards yes Print short header default IRAF data type 0 Blank val Type g to Save Parameters Rg see ap ae and Run Task i yes Transform xdim FITS to multigroup i yes Use old IRAF name in place of iraf_file 5 offset 0 Tape file offset Exit by typing q node ql for HELP To List Line Editing Commands ye Press Esc H Parameter Data Types What to Specify Parameters are either required or hidden and each parameter expects information of a certain type Usually the first parameter is required and very often it expects a file name Parameters are described in the online help for each task include reference to help Hidden parameters shown in parentheses in the online help and the Ipar and epar listings need not be specified at each execution because their default values frequently suffice Wise IRAF users will check the values of hidden parameters as they often govern important aspects of a task s behavior If you specify the wrong type of information for
365. to zero with a DQ value that contains all flags that were set CRIDCALLC is only applied to MULTIACCUM images For data taken in ACCUM or BRIGHTOBJ mode both the raw and calibrated images will contain cosmic rays and should be treated as with ordinary CCD data BACKCALC Predict Background This step computes a predicted background sky plus thermal signal level based on models of the zodiacal scattered light and the telescope plus NICMOS 3 16 J Chapter 3 Calibration instrument thermal background This step uses the BACKTAB reference table which contains the background model parameters Results of these predictions along with direct estimates of the background level from the data themselves are written to the BACKEST1 BACKEST2 and BACKEST3 header keywords The image data are not modified in any way At the time of this writing this step has not yet been implemented If there are future changes to the calibration procedures or software regarding the BACKCALC step these will be reported in the Space Telescope Analysis Newsletter STAN and posted on the NICMOS website WARNCALC User Warnings In this step various engineering keyword values from the _spt fits files are examined and warning messages are generated if there are any indications that the science data may be compromised due to unusual instrumental characteristics or behavior At the time of this writing this step has not yet been implemented Any future changes to the
366. try you should recheck the exact pixel scale using the information from the NICMOS History Tool and take the geometric distortion of the Cameras into account Finally it is important to note that precise astrometry with NIC3 can be complicated by three effects First for data taken outside the January or June 1998 refocus campaigns focus effects may affect the geometry of the focal plane Second data taken prior to January 1998 was usually vignetted see section 4 5 4 which can also distort the geometry Finally intrapixel sensitivity variations see section 5 3 and NICMOS ISR 99 005 Storrs et al can affect centroiding for undersampled point source images 5 5 PSF Subtraction Accurate PSF subtraction is a prime concern for an observer wishing to study faint features around bright objects Typical situations are a host galaxy harboring a bright quasar circumstellar nebulosity around a bright star faint companions of a bright star etc PSF subtraction for NICMOS data can be very effective especially for images from cameras 1 and 2 thanks to a few important features of this instrument e Cameras and 2 provide images which are diffraction limited and well sampled see figure 5 2 and figure 5 3 e The MULTIACCUM mode automatically provides sub exposures with different exposure times and calnica processing will use only unsaturated data values when constructing the calibrated image e Fora saturated bright central point sourc
367. ty of data formats such as OIF and GEIS as well as STIS and NICMOS 5 1 NICMOS 5 2 f Chapter 5 Data Analysis NICMOS FITS files and will in time replace the STSDAS tasks they render obsolete The new tasks fall into two major categories 1 General purpose utilities These tasks include tools for mathematical and statistical operations on science images and for analysis and dis play of reduced and raw data In most cases the new utilities extend existing routines to include error and data quality propagation These are the utilities of greatest interest to the user community Under this category are several tasks described in chapter 3 of the HST Introduc tion msarith mscombine msstatistics msjoin and mssplit along with a few other tasks we describe below ndisplay markdq mos display pstack pstats sampinfo nicpipe biaseq pedsky pedsub sampdiff and sampcum The first five are found in the package tool box imgtools mstools the remaining ones reside in the package hst_calib nicmos 2 Calibration oriented utilities These tasks generate reference files such as readnoise arrays dark files flatfields non linearity correction arrays and bad pixel arrays to feed the calibration database and to support the calibration pipelines The tasks are designed specifically for the calibration of NICMOS and are not particularly useful for the general observer The tools are mstreakflat msbadpix ndark nlin corr and msreadnois
368. u will probably want to create a new file that combines these quantities Several options for combining flux and wavelength information are available e resample This simple task resamples your flux data onto a linear wavelength scale creating a new flux file containing the starting wavelength of the new grid in the CRVALI keyword and the wave length increment per pixel in the CD1_1 keyword Encoding the wavelength information into these standard FITS header keywords Analyzing HST Spectra J INTRO 3 25 makes this format quite portable but the resampling process loses some of the original flux information In addition the error c2h and data quality cqh files cannot be similarly resampled limiting the usefulness of this technique e mkmultispec This task writes wavelength information into the header of a flux file while preserving all the original information It is therefore a better choice than resample for most applications and we describe it in more detail below e imtab An alternative to writing wavelength information into the header is to use the imtab task to create a table recording the wave length flux and if desired the error data corresponding to each pixel Many STSDAS tasks such as those in the STSDAS fitting package can access data in tabular form so we describe this approach in more detail as well mkmultispec The most convenient method of combining wavelength and flux information and one that has no
369. ument Overview W NICMOS 1 3 of which one is blank i e a cold opaque filter used in lieu of a dark slide Three of the other positions are occupied by either polarizers or grisms The remaining 16 positions of each filter wheel are occupied by broad medium and narrow band filters The list of these filters is given in the NICMOS Instrument Handbook The filters including polarizers and grisms cannot be crossed with each other and are used as single optical elements NICI and NIC2 each contain three polarizers whose principal axes of transmission are separated by approximately 120 degrees for the exact polarizer orientations and other details see section 5 7 of this manual and also chapter 5 of the NICMOS Instrument Handbook The spectral coverage is fixed for each camera The polarizers cover the wavelength range 0 8 1 3 um in NIC1 and 1 9 2 1 um in NIC2 Observations in the three polarizers of each camera are used to derive the Stokes parameters of linearly polarized light The filter wheel of NIC3 contains three grisms which can be used to perform slitless spectroscopy in the wavelength range 0 8 2 5 um The three grisms cover the range 0 8 1 2 um 1 1 1 9 um and 1 4 2 5 um respectively In NIC2 a coronographic spot is imaged onto the focal plane and provides a circular occulted region 0 3 in radius with a useful effective radius of 0 4 For coronographic imaging an acquisition sequence is required at the beginning of
370. user should be aware Each of these is discussed in further detail in the sections which follow the nature of the problem and its impact on NICMOS data is illustrated and possible processing solutions are considered The relevant sections for each anomaly are given in parentheses below It is expected that some aspects of NICMOS performance and anoma lies may be somewhat different in Cycle 11 and beyond with the NIC MOS Cooling System The discussions of data anomalies and appropriate solutions in this edition of the NICMOS Data Handbook are based on the properties and behavior of the instrument during Cycles 7 and 7N NICMOS users should carefully monitor develop ments and updates posted on the STScI NICMOS web pages when analyzing data taken in Cycle 11 and beyond NICMOS Problems to Watch Out For A Checklist e Bias and dark subtraction problems including residual shading section 4 1 2 section 4 1 5 variable quadrant bias or pedestal section 4 1 2 section 4 1 5 bias jumps or bands section 4 1 2 section 4 1 5 e Bars section 4 2 e Nonlinearity correction uncertainties new nonlinearity corrections section 4 3 1 non zero zeroth read correction section 4 3 2 uncorrected saturation section 4 3 3 NICMOS Dark Current and Bias IJ NICMOS 4 3 e Flatfield issues including color dependent flat fields section 4 4 e Pixel defects and bad imaging regions including Bad pixels section 4 5 1 G
371. ust come first When displaying sections of FITS image extensions you must specify the extension which also comes before the image section Figure 3 3 shows examples of displaying an image and an image section Analyzing HST Images IJ INTRO 3 9 Figure 3 3 Displaying Sections and Groups of an Image Display only a section of group 2 of the image 7 STSDAS Display group 2 of st gt display wOmw0502t cOh 2 503450 503450 entire Image frame to be written into 1 4 1 z1 _ 5 630896 z2 17 13277 se J STSDAS SAOimage st gt display wOmw0502t cOh 2 4 s frame to be written into 1 4 1 w0mu0502t cOhL2 MOMWOSO2TC2 4 zi 13 14832 z2 13 61855 CIRAF gt s J amp SAOimage wOmw0S02t cOhL2 WOMWOSO2TL2 41 lt IRAF sqrt
372. ut the position of problem pixels Although there is a DQ flag value 16 reserved for grot see table 2 2 the default MASKFILE reference images used by calnica do not include grot It would be straightforward however to make your own bad pixel mask combining the information about hot and cold pixels found in the current MASK reference file with the locations of pixels identified in the grot mask You may then reprocess from scratch using this new MASKFILE or you may add the new grot information into the DQ array of an already reduced data set When the dithered images are then combined by calnicb the flagged pixels will automatically be excluded Not all pixels affected by grot are unrecoverably ruined For pixels which are only partially obscured the effects of grot may flatfield out You NICMOS 4 28 Chapter 4 Anomalies and Error Sources 4 5 2 4 5 3 may wish to compare your flatfielded images with the grot masks to see which pixels have flattened well and which are potentially suspect Erratic Middle Column Row In each NICMOS camera there is one row or column which often deviates from others nearby In NIC1 this is row 128 in NIC2 it is column 128 and in NIC3 it is column 129 Adjacent rows or columns are sometimes affected to a lesser degree It is believed that this photometrically challenged column may be related to uncertainties in detector shading corrections The affected column row contains the first pixels rea
373. ute the final science image pixel value after rejection of cosmic ray and saturated pixels from the intermediate data As in the case of the SAMP array the TIME array can have different values at different pixel locations depending on how many valid samples compose the final science image in each pixel 2 1 3 NICMOS Data Files I NICMOS 2 9 In mosaic images _mos fits the TIME array values indicate the total effective exposure time for all the data from overlapping images that were used to compute the final science image pixel values Auxiliary Data Files The spt fits _trl fits _pdq fits asn fits and the _asc fits files are termed auxiliary data files They contain supporting information on the observation such as spacecraft telemetry and engineering data assessment of the quality of the observation calibration information and information on the associations present in the observations Association Tables The association tables _asn fits and _asc fits are FITS binary tables which are created when a particular observation generates an association of datasets see the discussion of Associations in appendix B In particular the _asn fits table is generated by opus and contains the list of datasets which make up the association e g from a dither or chop pattern The _asn fits tables are the inputs to the pipeline calnicb which creates the mosaiced or background subtracted images _mos fits files fr
374. ve HST data is to complete the form on the Web page at http archive stsci edu registration html Registration requests may also be sent to the HDA hotseat at archive stsci edu The PI of each HST proposal must request proprietary access for their data and for anyone else whom the PI wants to have access to it PI retrieval permission is not granted automatically for security reasons PIs wishing to allow others access to their proprietary data should make that request to archive stsci edu When registration is granted your account will be activated within two working days and you will receive your username and password via e mail Archive Documentation and Help The MAST web site provides a wealth of useful information including an online version of the HST Archive Manual available at http archive stsci edu hst manual Investigators expecting to work regularly with HST and other datasets supported by MAST should also subscribe to the MAST electronic newsletter by sending an e mail to archive_news request stsci edu and putting the single word subscribe in the body of the message Questions about the HDA can be directed to archive stsci edu or by phone to 410 338 4547 INTRO 1 4 W Chapter 1 Getting HST Data 1 2 Getting Data with StarView 1 2 1 1 2 2 Downloading and Setting Up StarView The latest version of StarView runs under versions 1 2 2 and later of Java and may be downloaded from http starview stsci edu Th
375. vers should note that the four chips are calibrated individually so these photometry keywords belong to the group parameters for each chip For all instruments other than NICMOS PHOTFLAM is defined to be the mean flux density F in units of erg cm s A that produces 1 count per second in the HST observing mode PHOTMODE used for the observation If the F spectrum of your source is significantly sloped across the bandpass or contains prominent features such as strong emission lines you may wish to recalculate the inverse sensitivity using synphot described below WF PC 1 observers should note that the PHOTFLAM value calculated during pipeline processing does not include a correction for temporal variations in throughput owing to contamination buildup Likewise FOC observers should note that PHOTFLAM values determined by the pipeline before May 18 1994 do not account for sensitivity differences in formats other than 512 x 512 To convert from counts or DN to flux in units of erg cem s A multiply the total number of counts by the value of the PHOTFLAM header keyword and divide by the value of the EXPTIME keyword exposure time You can use the STSDAS task imcalc to convert an entire image from counts to flux units For example to create a flux calibrated output image outimg fits from an input image inimg fits 1 with header keywords PHOTFLAM 2 5E 18 and EXPTIME 1000 0 you could type st gt imcalc inimg fits 1 outimg fits im1l
376. which they are subtracted This can introduce a sort of pattern noise in the images which is apparently random but actually affects the pixel to pixel statistics of reduced data in a systematic way In general this is not a limiting source of noise in NICMOS data but it can set a limit to the pixel to pixel noise achievable with images reduced by calnica using the standard reference files In the newer temperature dependent synthetic dark reference files now available via a WWW based tool see section 4 1 5 below a much larger number of dark exposures has been averaged to produce the final product thus reducing this pixel to pixel component of the dark frame noise to a negligible level Systematic Uncertainties in the Synthetic Darks The dark current pedestal adds some uncertainty to the synthetic darks since on orbit dark frames are used to generate the calibration reference files In essence the pedestal makes it difficult to establish the absolute DC level of the dark current However every effort was made to minimize the effects of the pedestal when making the reference files currently in the database Also during the lifetime of the instrument no temperature dependence was included in the dark files used in the calibration data base As discussed elsewhere see section 4 1 2 and section 4 1 5 this can lead to systematic bias subtraction errors primarily due to problems with the shading correction New dark reference fi
377. with respect to the principal axes of transmission For POLOS the brightest ghost is found roughly 10 35 pixels away from the target position and a second one at 16 70 pixels It is possible that for a brighter object more ghosts would appear in the same angle and direction POL120S images appear to be ghost free For POL240S ghosts appear 10 54 pixels from the source position and 18 80 pixels with the possibility of more appearances for brighter targets Figure 4 10 Optical ghosts in NIC1 polarizers POLOS POL120S POL240S Ordinary non polarimetric NICMOS images of bright sources may have very faint filter ghosts which result from back reflections off the faceplate and the filters The position of the ghosts changes from one filter to another They are roughly 8 magnitudes fainter than the star which produces them The ghosts cannot be completely subtracted from the field unless the reference PSF is at the exact same location as the star They are typically seen as a residual in the PSF subtracted images and look like large donuts because they are out of focus reflected images Cures No true cure is possible be aware that such ghosts may exist their positions are predictable If images are available with multiple spacecraft roll angles the ghosts may be masked out before combining the data Cosmic Rays of Unusual Size IJ NICMOS 4 37 4 7 Cosmic Rays of Unusual Size As with CCDs cosmic ray CR
378. xample gt hedit n4xjl3jwq_raw fits 0 EXPTIME n4xjl3jwq_raw fits 0 EXPTIME 0 625648 gt hedit n4xjl3jwq_spt fits 0 CMD EXP n4xjl3jwq_spt fits 0 CMD_EXP 0 255647987127 The SAMPTIME keywords have to be changed in both SCIENCE groups of the raw uncalibrated imageset _ raw fits before calnica processing Reducing and Co adding Coronagraphic Images The OPUS pipeline will combine multiple coronagraphic exposures using calnicb This can cause difficulties however for coronagraphic data analysis If the individual images that form a mosaic require registration some smoothing will be introduced by the bi linear interpolation that is used by calnicb to shift the images Even if the images are well registered to begin with slight differences in the diffraction pattern due to movement of the coronagraphic hole may cause the calnicb cross correlation routine to compute non zero offsets between the various images This will lead to misregistration and again some smoothing One way around this problem is to force calnicb not to shift any of the images before averaging them together This can be accomplished by adding columns of XOFFSET and YOFFSET values to the input association table _asn fits used by calnicb and setting their data values to zero However in general PSF subtraction is best performed with individual images and not with the mosaic image Coronagraphic Reductions IJ NICMOS 5 39 Pedestal Removal
379. xel scale arcseconds per pixel is not set by the drizzling procedure and should be determined by consulting the NICMOS History Tool as explained above The appropriate value to use with the drizzled images is the geometric mean of the X and Y scales specified by the web pages or History Tool i e V Sy x Sy Absolute Astrometry As with all HST instruments determining the absolute astrometry in NICMOS images to good accuracy requires precise astrometry from some external source for some object or objects within the field of view The absolute pointing reference given by world coordinate system WCS information encoded in NICMOS image headers is derived from the HST Guide Star Catalog GSC positions for the stars used to guide the observations Although the GSC positions and hence the WCS astrometry PSF Subtraction HJ NICMOS 5 23 are generally good deviations by as much as 2 arcseconds from an absolute celestial reference frame e g FK5 are not uncommon The WCS information provided with NICMOS images does account at least to first order for the nominal pixel scale camera orientation and even the X and Y pixel scale differences of the cameras It does not however include any higher order corrections for geometric distortion Therefore relative positions measured using the WCS e g with the IRAF tasks imexam or rimcur are fairly accurate even if the absolute pointing reference may not be exact For precision relative astrome
380. xels in a quadrant are saturated there should be no noticeable effect on biaseq Also residual shading may result in a bias which changes from readout to readout but is not constant across the quadrant and this may also cause problems for biaseq In particular residual shading can improperly trigger the bias jump finding algorithm If there is residual shading in the images it should be removed with a temperature dependent shading correction see Residual Shading on page 4 14 before running biaseq If biaseq is run without doing this the user should at least disable the bias jump finding option The biaseq help pages give further information about this task and its parameters pedsky For NICMOS images of relatively blank fields free of very bright or large sources which fill a substantial portion of the field of view the pedsky task may be used to measure and remove an estimate of the sky background and quadrant dependent residual bias or pedestal The task depends on having a large fraction of the image filled by blank sky and thus may not work well for images of large extended objects or very crowded fields NICMOS 4 16 J Chapter 4 Anomalies and Error Sources Pedsky runs on a single science image i e not on all the separate readouts of a NICMOS MULTIACCUM file It operates only on the SCI 1 extension which is appropriate when the task is run on e g the _cal fits images that are the final product of the calnica c
381. ximum N 26 GLOBAL HEADER EXT 0 i SCIENCE IMAGE SCIENCE IMAGE SCIENCE IMAGE EXT SCI 1 or 1 SCIENCE IMAGE EXT SCI 2 or 6 EXT SCI3 or 11 EXT SCIN or 5 N 1 1 ERROR EXT ERR 1 or 2 ERROR EXT ERR 2 or 7 ERROR EXT ERR 3 or 12 ERROR EXT ERR N or 5 N 1 2 DATA QUALITY FLAGS EXT DQ 1 or 3 DATA QUALITY FLAGS EXT DQ 2 or 8 DATA QUALITY FLAGS EXT DQ 3 or 13 EXT DQN or 5 N 1 3 eal DATA QUALITY FLAGS 4 SAMPLES EXT SAMP 1 or 4 SAMPLES EXT SAMP 2 or 9 SAMPLES EXT SAMP 3 or 14 SAMPLES EXT SAMPN or 5 N 1 4 INTEGRATION TIME EXT TIME 1 or 5 INTEGRATION TIME EXT TIME 2 or 10 INTEGRATION TIME EXT TIME 3 or 15 INTEGRATION TIME LA hi ma ma ma EXT TIME N or 5 N 1 5 p The following sections explain the contents and origin of each of the five image arrays in each imset in more detail Science Image This image contains the data from the detector readout In ACCUM and BRIGHTOBJ modes the image received from the instrument is the result of subtracting the initial from the final readouts of the exposure In MULTIACCUM mode the images received are the raw unsubtracted data corresponding to each detector readout In raw datasets the science array is an integer 16 bit image in units of DNs counts In calibrated datasets it is
382. xis Angle between moon and V1 axis Commanded FGS lock FINE COARSE GYROS UNKNOWN UT date of start of the observation dd mm yy or yyyy mm dd UT time of start of the observation hh mm ss Exposure start time Modified Julian Date Exposure end time Modified Julian Date Total integration time sec Exposure interruption indicator e g NORMAL Instrument Configuration Information NICMOS camera used in the observation 1 2 or 3 NICMOS 2 12 Chapter 2 Data Structures Keyword Name PRIMECAM FOCUS APERTURE OBSMODE FILTER NUMITER NREAD NSAMP SAMP_SEQ FOMXPOS FOMYPOS NFXTILTP NFYTILTP NPXTILTP NPYTILTP NPFOCUSP TIMEPATT READOUT SAMPZERO HCLKRATE VIDEO_BW ADCZERO ADCGAIN PHOTMODE PHOTFLAM PHOTFNU PHOTZPT PHOTPLAM PHOTBW SAA_EXIT SAA_TIME SAA_DARK SAACRMAP MASKFILE NOISFILE NLINFILE DARKFILE FLATFILE PHOTTAB BACKTAB Meaning NICMOS Prime Camera during the observation for internal parallels In focus camera for this observation Aperture used in the observation NICi NICi FIX NIC2 CORON Observing mode MULTIACCUM ACCUM Filter or grism used Number of iterations of the exposure Number of ACCUM initial and final readouts Number of MULTIACCUM or RAMP samples MULTIACCUM exposure time sequence name X offset of the Camera FOV using NICMOS FOM arcsec Y offset of the Camera FOV using NICMOS FOM arcsec FOM X tilt position arcsec FOM Y tilt position arcsec PAM X tilt position ar
383. y HDU are header keywords There are no image data in the primary HDU The keywords in the primary header are termed global keywords because they apply to the data in all of the file extensions The organization and location of header keywords is explained in detail later in the chapter NICMOS Data Files IJ NICMOS 2 5 Table 2 1 NICMOS Science Data File Contents Header Data Extension Unit Name imset Contents Data Type Primary Extension 0 N A N A Global keywords no data N A Extension 1 SCI 1 Science image raw 16 bit int calibrated float Extension 2 ERR 1 Error sigma image float Extension 3 DQ 1 Data Quality image 16 bit int Extension 4 SAMP 1 Number of Samples image 16 bit int Extension 5 TIME 1 Integration Time image float Extension 6 SCI 2 Science image raw 16 bit int calibrated float Extension 7 ERR 2 Error sigma image float Extension 8 DQ 2 Data Quality image 16 bit int Extension 9 SAMP 2 Number of Samples image 16 bit int Extension 10 TIME 2 Integration Time image float Figure 2 1 Data Format for ACCUM BRIGHTOBJ and ACQ Modes Ta EXT 0 GLOBAL HEADER O SCIENCE IMAGE EXT SCI 1 or 1 ERROR EXT ERR 1 or 2 Ler P SAMPLES DATA QUALITY FLAGS EXT DQ 1 or 3 o EXT SAMP 1 or 4 INTEGRATION TIME EXT TIME 1 or 5 NICMOS 2 6 Chapter 2 Data Structures Figure 2 2 MULTIACCUM Mode Data Format Ma
384. y clicking the Quick button at the top left of StarView As an example of the use of the Quick Search option we will request all available WFPC2 data for the galaxy M87 This is done by typing WEPC2 and M87 in the Instrument and Target Name cells of the Qualifications section then clicking the Search button at the top left of the StarView window The results of the search will then be displayed in the bottom panel of StarView as shown in figure 1 1 These results include the dataset name instrument name R A and Dec of the target and the instrument aperture used Note that these parameters could also have been specified in the Qualifications section as can other parameters including proposal I D number proposal P I name and image central wavelength corresponding to particular instrument filters or gratings Figure 1 1 Results of StarView Quick Search for WFPC2 files of M87 File Edit View Searches Comment Window 2 SISIS 2 2i2 x12 1212 3 2 8 e Sel Enter qualifications for Quick Search Load Qualifications Save Qualifications Clear Qualifications Label Qualification click cell to edit Database Field Name ogical Type Dataset Name sci_data_set_name datasetname Radius degrees 0 10 sci_ra sci_dec radius RA sci_ra a Dec sci_dec decl Instrument sci_instrume instrument Flag sci_expflag expflag sci_aper_1234 se T Results for Quick Search Proposal ID
385. ynthetic spectrum to calculate form counts Form for output data func effstim Function of output data vzero List of values for variable zero output append none Output table name no Append to existing table wavetab Wavelength table name result 0 Result of synphot calculation for form refdata Reference data mode a sy gt epar calcphot obsmode nicmos 3 212n dn Instrument observation mode spectrum gauss 21280 40 unit 1E 13 flam Synthetic spectrum to calculate form counts Form for output data func effstim Function of output data vzero List of values for variable zero output none Output table name append no Append to existing table wavetab Wavelength table name result 0 Result of synphot calculation for form refdata Reference data mode a The examples in figure 5 1 compute the countrate in the NIC3 F212N filter for a Hy 2 12 micron emission line having a gaussian profile of 40 Angstroms and a peak flux of 1 0 x 10713 erg sec cm A The integrated flux will then be 4 2 x 107 erg sec cm In the first example the H emission line is at zero redshift and centered on the filter while in the second example the line is redshifted by 80 Angstroms If the emission line is centered on the filter the H flux will produce 7421 1 DN sec while the countrate will be 90 of this value i e 6662 3 DN sec for the redshifted emission line The expr
386. ype man saoimage in Unix or help saoimage in VMS The example in figure 3 2 shows how you should display an image for a first look By default display automatically scales the image intensity using a sampling of pixels throughout the image During your first look you may want to experiment with the scaling using the zscale zrange zl and z2 parameters The zscale parameter toggles the autoscaling Setting zscale and zranget tells the task to use minimum and maximum values from the image as the minimum and maximum intensity values To customize your minimum and maximum intensity display values set zscale zrange z1 to the minimum value and z2 to the maximum value that you want displayed For example im gt disp w0mw0507v cOh 1 zrange zscale z1 2 78 z2 15 27 Notice in figure 3 2 that when you run display the task shows you the z1 and z2 values that it calculates You can use these starting points in estimating reasonable values for the minimum and maximum intensity display parameters If you want to display an image with greater dynamic range you may prefer to use logarithmic scaling However the log scaling function in SAOimage divides the selected intensity range into 200 linearly spaced levels before taking the log The resulting intensity levels are rendered in a linear rather than logarithmic sense You can often obtain better results if you create a separate logarithmic image to display One way to create a logarithm

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