Data Reduction Manual
Contents
1. a P are roa inate Bel PTY ee E ats Siar be ee ee a oe Ni 4000 000 sowo 10000 12000 14000 18000 18000 0000 T Figure 2 8 Average of sky images in the Pa filter left panel showing evident fringes After subtraction of dark frame right panel 3 At this point most of the dark current will be removed except for occasional mavericks but the frame still has the low spatial frequency structure and the central pupil ghost Dividing by the dome flat and running fixpix with the bad pixel mask will remove most of the structure and clean up the image Fig 2 9a 4 The fringe template for rmfringe has ideally a minimum value near zero so one can at this point subtract off a constant value to achieve this Running fmedian with a fairly small box 3 x 3 appears to enhance the S N without affecting the spatial resolution of the template Fig 2 9b WHIRC Data Reduction Manual Version 1 03 2009 August 24 14 For comparison we show in Fig 2 10 fringe templates for the PaB45 and H filters to show the need for filter and time specific fringe information While the PaB45 pattern seems similar to the Pa pattern one can see a phase difference in the central fringe The fringe visibility in the H band varies suggesting that several emission lines contribute to the fringes l Ta ae 30 Figure 2 9 left panel Pap sky image from Fig 2 8b after dividing by a dome flat and cleaning up bad pixels Some of the palmprint can2. distortion correction when using PSF fitting photometry WHIRC Data Reduction Manual Version 1 03 2009 August 24 20 100 J00 0 J0 1000 1500 e000 Figure 3 3 Mosaic of five images of the M13 field in the H band The images offset by 50 arcsec in a pattern were corrected using geotran prior to mosaicking The 2MASS point source catalog is overlaid on the field Except for multiple sources mistakenly cataloged as a single 2MASS source the positional fit is excellent to the edge of the field WHIRC Data Reduction Manual Version 1 03 2009 August 24 21 4 0 Appendices 4 1 Appendix A Observational Test of Pupil Ghost Removal On the apparently photometric night of 9 July 2009 UT we tested the pupil ghost removal technique described in section 2 4 2 by sampling a region approximately 80 arcsec square centered on the array An arbitrary star Ks 11 on the outskirts of M13 was measured using four 5 x 5 dither sequences of amplitude 10 arcsec each of which was offset by 18 arcsec in both RA and DEC from the center of the array in the four possible directions This gave high spatial sampling of the area around the center of the pupil ghost approximately 1032 1002 on the array The experiment was done in the Ks filter where the pupil ghost is most pronounced The focus was checked between each of the four sequences to ensure that the image quality did not drift significantly during the experiment seeing was modest 0 6 0 7 a
3. Except in very crowded fields or those with extended structure one is also measuring the sky level on every pixel by moving the sources around after each individual exposure 2 0 Data Preparation During a night of observing one will generally obtain the following types of observations 1 Flatfields We recommend a series of dome flats in each of the filters used at least 10 each with the lights on and an equal number with the lights off The latter will serve as the bias and dark subtraction One can also generate sky flats using sky frames generated from the observations and a series of darks of the same integration time Sky flats may be more used for reduction in the H and Ks filters where there is significant thermal background One may also use twilight observations for sky flats in the J filter Nighttime observations in the narrowband filters will generally not accumulate sufficient flux for high S N sky flats and even twilight flats in the narrowband filters must be WHIRC Data Reduction Manual Version 1 03 2009 August 24 3 obtained within a fairly narrow time window We strongly suggest that observers who generate sky flats also obtain dome flats as a backup 2 Science Observations These can be a series of dithered observations on the source field for standards and pointlike sources or a set of dithered observations on the source and a set of dithered observations at an off source sky location 3 Darks These are not real
4. integer output format So for the Fowler 4 data only imarith tr fits 4 tr fits will do this in place A safer way to do this is to write all of the data to a list generate a list of the Fowler samples for all of the data then divide files tr fits gt trlist hselect trlist fowler yes gt flist imar trlist flist trlist 3 Linearity correction As the wells in the array fill up the gain changes slightly resulting in a slightly sublinear response which is approximately 4 at 38000 ADU We have carried out a quadratic fit to the linearity function for 0 7 v bias up to a value of 38000 ADU By inverting this function one can derive a linearity correction function so that the corrected signal S is related to the raw signal S by S S A B S C S where A 1 0000 A 1 0000 B 1 29 x 10 0 004227 C 2 506 x 107 C 0 02691 The IRAF task irlincor is specifically designed to carry out this correction the coefficients A B and C above are the irlincor values Jt is critical that linearity correction be performed on the raw data prior to any sky or dark subtraction but after any scaling for multiple Fowler sampling Do an epar irlincor and enter the above values for A B and C into the parameter file control D to exit then irlincor tr fits tr lc fits 4 At this point you will have three sets of data you may want to archive the original raw data somewhere and the trimme
5. result of multiple internal reflections within the optical train Unlike the MOSAIC imager pupil ghost which arises within the corrector and appears as a highly defocused image of the telescope exit pupil the WHIRC ghost probably arises within both the collimator and camera optics and shows up as a broad central peak Fig 2 3 Because the pupil ghost arises from the total background flux it is seen in both sky and dome flat images Under reasonably constant sky background conditions the technique of sky subtraction will effectively remove the pupil ghost from the science data However the lights on lights off technique for producing dome flats will subtract off dark current and any common mode signal such as thermal emission from the telescope and WTTM optics in the K band but not the pupil ghost from the flatfield lights As a result the pupil ghost appears in the reduced flat Because this does not represent a true response peak using a flatfield with the pupil ghost will result in an artificially reduced signal level in the central region of the detector It is therefore necessary to remove this artifact for accurate calibration of science data The IRAF package mscred designed for reducing MOSAIC data has routines for modeling the pupil ghost and removing it from the data Unfortunately the modeling task works only for ghosts with a central obscuration as seen with MOSAIC and 1s not effective for the centrally peaked WHIR
6. still be seen right panel After subtracting the background and smoothing one has an adequate fringe template The white blobs are probably artifacts from bright stars in the original images which were not completely removed by the median filtering 100 200 300 400 500 600 700 600 900 1000 20 40 60 60 100 120 Figure 2 10 Fringe templates derived from sky data in the PaB45 left panel and H right panel filters Note the phase shift in the central fringe between the PaB Fig 2 9b and PaB45 templates and the amplitude modulation in the H template 5 Using the appropriate fringe template the task rmfringe can then be used to remove the fringes Figure 2 11 illustrates this for a H band sky on a night where fringing was WHIRC Data Reduction Manual Version 1 03 2009 August 24 15 evident In practice one would operate on a sky subtracted image where the fringe pattern should be much less evident 4500 5000 5500 6000 6500 7000 7500 6000 8500 9000 500 5000 5500 6000 6500 7000 7500 5000 6500 3000 Fig 2 11 H band sky image left panel on a night when fringing was evident After processing with the rmfringe task the fringes are almost completely eliminated right panel 3 0 Data Reduction 3 1 Standards or Pointlike Objects 1 One will generally have several images of the field with different telescope pointings Depending on the sky stability the sky level may be somewhat different in each of the images 2 Create a sk
7. yl y2 thus the entry 326 349 255 278 identifies the region between columns 326 and 349 and rows 255 and 278 as bad This technique is useful for identifying regions such as PEDs section 2 4 1 4 which produce some signal and may not be completely identified through the flatfield ratio technique RAF reduction tasks will accept either a bad pixel image or file or both 2 4 1 4 Photo emitting Defects Photo emitting defects PEDs are generally pixels which become shorted during the hybridization process They draw significant current during the bias reset and emit light PEDs are generally identified during the testing stage by the vendor and cauterized using a laser This produces a region of limited sensitivity approximately 20 pixels in diameter surrounded by a bright annulus The WHIRC detector has at least two PEDs centered near 337 266 and 839 1804 The first of these appears to still emit some light and may be responsible for the region of elevated dark current known as the palmprint Because these regions are not completely dead the technique of generating a bad pixel image by the flatfield ratio technique does not seem to encompass the entire PED so using a bad pixel file to identify these regions is good insurance 2 4 2 Pupil Ghost As noted in section 2 2 WHIRC images feature a bright region near the center of the detector This pupil ghost is a common feature of on axis refractive optical imagers and is a
8. 50 1250 remains WHIRC Data Reduction Manual Version 1 03 2009 August 24 12 The pupil template can then be used with the task mscred rmpupil to remove the pupil ghost from the flat Fig 2 7 A representative pupil template whircpupil fits can be downloaded from the WHIRC webpage although observers may wish to create their own The pupil mask pupmask pl also on the webpage is a four line file which restricts the rmpupil task to the central 600 lt 600 pixel region The outtype parameter should be set to sdiff since one is subtracting the ghost and the 5 pixel smoothing for row and columns seems to be good The extfit parameter should be set to null because the WHIRC files are not multi extension FITS Observational tests appear to verify this strategy to be effective in removing the effects of the pupil ghost Appendix A 2 4 3 Fringes In at least three of the WHIRC filters PaB PaB45 and H Newton s Rings fringes have been seen in on sky images These almost certainly arise from OH emission lines in the atmosphere and are thus not seen in dome flats although they may appear in H band sky flats The optical configuration within WHIRC which produces these fringes is not known but they are textbook Newton s Rings centered at the same location on the detector in all filters where they are seen The PaB and PaB45 fringes appear monochromatic whereas the H band fringes show amplitude modulation sugge
9. C ghost Applying a smoothing function using a WHIRC Data Reduction Manual Version 1 03 2009 August 24 Il task such as fmedian appears to be a reasonable approach but a careful inspection of the flats in Fig 2 3 shows a bright region in the vicinity of 1250 1250 which appears in both the J and Ks flats at the same apparent level and probably represents a true response variation which must remain in the final flat Since the pupil ghost is stronger at Ks than at J the ratio of the reduced flatfields after bad pixel correction Fig 2 6a may be an accurate template for the ghost the J band fingerprint lies well outside the region of interest Isolating the central 800 x 800 pixel region and smoothing with fmedian using a 21 x 21 pixel box produces a promising pupil image template Fig 2 6b Using gauss with sigma 31 gave a similar result observers may want to try both of these strategies 0 94 0 96 0 98 1 1 02 1 04 1 06 1 08 1 1 1 12 11 0 0 01 0 02 0 03 0 04 0 05 0 06 0 07 0 08 0 09 Fig 2 6 left panel Ratio of reduced dome flats in Ks and J Note that the bright region near 1250 1250 cancels out of the ratio suggesting it is a response variation common to both wavelengths right panel The central 800 x 800 pixel region of the ratio smoothed to 21 pixels using fmedian Fig 2 7 Dome flat for Ks before left panel and after right panel removal of bad pixels and the pupil ghost Note the bright region near 12
10. WIYN High Resolution Infrared Camera WHIRC Quick Guide to Data Reduction Dick Joyce Version 1 03 2009 August 24 WHIRC Data Reduction Manual Version 1 03 2009 August 24 l ACRONYMS AND ABBRE VIA TIONS sacha dianacatess season sled iaacuadbabeesaensseeni en odo aa a a ais 2 1 0 INTRODUCTION 2 0 DATA PREPARATION 3 1 32 3 3 4 1 INITIAL STEPS GENERATING DOME FLATS GENERATING SKY FLATS ARTIFACT REMOVAL 2 4 1 BAD PIXELS 2 4 2 PUPIL GHOST 2 4 3 FRINGES 3 0 DATA REDUCTION STANDARDS OR POINTLIKE OBJECTS EXTENDED OBJECTS OR CROWDED FIELDS COMBINING IMAGES INTO A MOSAIC 3 3 1 LARGER MOSAICS 3 3 2 DISTORTION CORRECTION 4 0 APPENDICES APPENDIX A OBSERVATIONAL TEST OF PUPIL GHOST REMOVAL Acronyms and Abbreviations DHE FITS GUI IAS IRAF MOP PAN OA TCS WHIRC WIYN WHOCS WHOMP WTTM Detector Head Electronics MONSOON system Flexible Image Transport System image standard Graphical User Interface Instrument Adapter System Image Reduction and Analysis Facility MONSOON Observing Platform Pixel Acquisition Node computer controls MONSOON Observing Associate Telescope Control System WIYN High Resolution InfraRed Camera Wisconsin Indiana Yale NOAO Observatory consortium WHIRC Observation Control System WHIRC Observation Manager and Planner WIYN Tip Tilt Module WHIRC Data Reduction Manual Version 1 03 2009 August 24 WIYN High Resolution Infrared Camera WHIRC Data Reduction Gu
11. amp on images one can scale the images using the mean of a large subregion 500 1500 500 1500 to take out the effects of any drift in the lamp intensity during the observation The lamp off data generally do not require scaling since the numbers are small WHIRC Data Reduction Manual Version 1 03 2009 August 24 6 10000 11000 12000 13000 14000 15000 16000 300 1400 1500 1600 1700 1600 1900 2000 2100 2200 Figure 2 2 Flatfield images at Ks with the flat lamp on left panel and off right panel Note there is substantial thermal background flux even with the lamp off 2 Subtract the lamp off from the lamp on image to yield a dark bias subtracted flat 3 It is useful to normalize the flats to 1 0 using a fairly large subregion such as 500 1500 500 1500 to keep the science data values from changing too much after the flatfielding operation Since all data science and calibrations are divided by the same flat the scaling integrity should be preserved 4 Itis also worthwhile to use the IRAF routine imreplace to eliminate very small or negative numbers from the flat so one does not get enormous numbers in the flatfielded science images I typically use a replacement value of 1 0 and an upper limit of 0 02 keeping the lower level at INDEF 5 Correct for artifacts if necessary Since this procedure may apply to both dome flats and sky flats this is discussed separately in section 2 4 At the end of this procedure
12. bove except that the iralign task WHIRC Data Reduction Manual Version 1 03 2009 August 24 19 works in the overlap region between two adjacent images only The only precondition is that the input images have some spatial overlap with their neighbors The irmosaic task combines the input images into a single N x M mosaic in the same geometry that they were taken on the sky One then uses iralign to identify pairs of stars common to adjacent images until all nearest neighbors have been matched The separations between these stars in the mosaic image is written to a database The irmatch2d task shifts the images in the original mosaic to that the adjacent stars match up creating a single composite image NOTE Because WHIRC is designed to exploit the good seeing at WIYN particularly once WTTM is operational it is expected that it will be used mostly for deep mapping of relatively small areas Other instruments such as NEWFIRM are better suited to wide field surveys 3 3 2 Distortion Correction Because WTTM utilizes off axis reflective optics the plate scale is different in the x and y coordinates on the detector 0 0969 and 0 1002 arcsec pixel respectively In addition there is a small amount of field distortion at the input to WHIRC The distortion is asymmetric keystone and is less than 1 The additional distortion from WHIRC is very small and is negligibly dependent on wavelength During the design of WHIRC the entire optical
13. d tr fits data can be deleted the trimmed scaled linearized data lc fits will be used for reduction 5 The IRAF script wprep cl which can be downloaded from the WHIRC web page will automatically carry out all of these steps In addition it will check the ROTOFF value in the image header and recalculate the WCS parameters so that the sky coordinates are WHIRC Data Reduction Manual Version 1 03 2009 August 24 5 correctly displayed on the image display ROTOFF is normally 0 0 but at some telescope orientations the WIYN instrument rotator has to rotate by 180 degrees because of the limited cable loop Also observers may intentionally rotate the instrument to a non cardinal orientation to fit an elongated target onto the array These offsets are properly recorded in the ROTOFEF keyword but not in the raw image display at the telescope After executing wprep cl the celestial coordinates will be properly oriented on the image 5 1 Download the script wprep cl from the WHIRC webpage and put it in a directory such as the IRAF home directory containing the login cl file e g home user iraf 5 2 Edit the loginuser cl file to source the task when IRAF is started up task wprep home user irat wprep cl 5 3 Put the raw WHIRC images into a list e g files fits gt inlist We strongly recommend that you keep a backup copy of the raw images prior to any reduction to be safe 5 4 Execute the script with wprep You will be promp
14. e needed to ensure good overlap of the stars different images section 3 3 2 3 2 Extended Objects or Crowded Fields 1 As with the pointlike fields one should have several dithered images of the science field but also a set of dithered images taken at a not too distant sky position relatively devoid of stars 2 Combine the off target sky images as above using median filtering 3 Subtract the sky image from each of the target images to yield the sky subtracted image 4 Flatfield the sky subtracted images as above 5 One may analyze the results from each image separately or combine them using upsqiid or other custom routines 3 3 Combining Images into a Mosaic For IRAF users the upsqiid package written by Mike Merrill can be used to align and combine the images into a single image This is primarily useful for deep imaging where one is observing the same field with relatively small dither amplitudes since it relies on locating star s common to all images for alignment Although this package was written primarily for data from the 4 color imager SQIID the routines for aligning and combining individual images into a mosaic are applicable for WHIRC images A description of the upsgiid package as well as instructions for downloading the package into IRAF can be found at http www noao edu kpno sqiid upsqiudpkg html Three basic tasks which have been found useful for combining images are xyget Find common stars i
15. eter outtype was set to sdiff since one is subtracting the ghost and the column and line smoothing were set to 20 The resulting flats were the nopupil flats WHIRC Data Reduction Manual Version 1 03 2009 August 24 22 The sky subtracted images were flattened with both the uncorrected and nopupil flats yielding three datasets of 100 images each e Sky subtracted unflattened images e Uncorrected flattened images e Pupil corrected flattened images The selected star was measured using apphot with a fairly large 4 arcsec diameter aperture to minimize the effects of seeing or focus drifts for all three datasets The X and Y coordinates were translated to radial distance from the pupil ghost center at 1032 1002 this was used as the abscissa for plotting the measured signal levels Fig 4 1 The figure illustrates that the uncorrected flat does have the anticipated effect of reducing the point to point scatter in the measured flux but introduces a very significant 0 15 mag systematic artifact as a result of the pupil ghost The additional illumination in the ghost results in signal levels which are too faint The bottom panel of the figure demonstrates that the pupil removal procedure has effectively eliminated this artifact The rms scatter in the pupil corrected flattened images 0 024 mag is significantly less than that in the unflattened images 0 035 mag but is still larger than earlier tests with a 9 x 9 ras
16. his pretty much restricts nighttime observations to the H and Ks filters Twilight flats can be taken in the J and perhaps narrowband filters but the rapid onset of twilight in the infrared leaves limited time for this procedure H band sky flats may show fringing from the OH lines which will complicate the process section 2 4 3 2 Take a series 10 of dark frames using the OPAQUE filter at the same integration time as used for the observations being used to generate the sky flat this will subtract out any bias and or dark current Average the dark frames perhaps with average sigma clipping to prune out maverick pixel values WHIRC Data Reduction Manual Version 1 03 2009 August 24 S 3 Generate a sky image as described in section 3 1 Ideally one should use a large number of images 10 or more at more or less the same airmass with several thousand ADU of background 4 Subtract the averaged dark frame from the sky frame Normalize and correct for artifacts as for the dome flats 2 4 Artifact Removal WHIRC images contain several types of artifacts some of which are intrinsic to the detector others of which result from multiple reflections within the optics Correction for these remains a work in progress but some techniques are discussed in this section Because infrared arrays utilize a unit cell architecture the pixels are effectively independent of each other unlike those in a CCD 2 4 1 Bad Pixels Like all array
17. ide 1 0 Introduction This document is a quick guide to reducing data taken with the WIYN High Resolution Infrared Camera WHIRC Data reduction is a highly personal process so one should keep in mind the procedures described here are biased by the author s personal preferences and experience Many WHIRC users may have their own possibly superior means of reducing data or use reduction platforms other than IRAF Suggestions from the user community will be welcomed As noted in the User Manual the high and variable sky and telescope background in the infrared results in background flux levels on the detector which are often far larger than the astronomical signals which one is attempting to detect In addition the architecture of infrared arrays is one of independently read out pixels rather than the charge transfer utilized with CCDs Dead or hot pixels with high dark current therefore show up as isolated features on infrared images As with CCDs observations of a uniformly illuminated target flatfields are used to calibrate the pixel sensitivity function of the images Both the high sky background and the problem of isolated dead or hot pixels are addressed by taking multiple images of a field moving the telescope a small distance between integrations This technique referred to as nodding or dithering results in sampling a target at several locations on the array so the effects of bad pixels can be minimized
18. ly required for data reduction because the process of sky subtraction will also subtract out any dark current or bias structure However a series of at least 10 short 5 s darks is a useful diagnostic for evaluating the read noise If one generates sky flats darks at the same integration time are needed 2 1 Initial Steps Independent of the reduction platform or individual techniques used for reduction there are several steps which should be carried out on all of the data frames prior to any reduction 1 Trimming The raw data frames are 2144 x 2050 pixels in size with 96 columns of reference pixels Fig 2 1 on the right side and two rows at the top which are presently of no use and will just make things ugly during the reduction We suggest trimming these off of all of the data frames e g imcopy fits 1 2048 1 2048 fits tr fits 600 600 1000 1200 1400 1600 600 700 600 300 1000 1100 1200 1300 1400 Figure 2 1 Raw Ks band image before left panel and after right panel trimming There is one bad column 97 and row 286 on the detector The bright spot in the center of the field is the pupil ghost WHIRC Data Reduction Manual Version 1 03 2009 August 24 4 2 Scaling If any of the data were taken with Fowler 4 mode the pixel values must be normalized by a factor of 4 prior to any linearity correction The Fowler 4 mode adds all of the four readouts but does not divide by 4 to avoid possible noise digitization in the
19. n the images and create a registration database zget Find intensity offsets from overlap regions in the registration database nircombine Combine the registration database into a composite image For mosaics involving large dither amplitudes distortion correction may be advisable to ensure proper overlap of the star images in different fields See section 3 3 2 for details WHIRC Data Reduction Manual Version 1 03 2009 August 24 17 600 700 600 300 1000 1100 1200 1300 1400 600 700 600 300 1000 1100 1200 1300 1400 Figure 3 1 upper left Image of the NGC 7790 field at Ks after trimming This is one of nine images of the field taken in a 3 x 3 grid with 50 arcsec spacing upper right Sky image obtained by combining the nine input images with a median filtering algorithm lower left Difference of the top two images Note that the sky subtraction reduces the residual background to near zero lower right After flatfielding the nine images are combined into a single composite using the upsqiid package Note that the noise is higher in the periphery of the image where only a single image contributes to the mosaic Combining images with extended nebulosity may require some individualized fine tuning of the intensity levels since the algorithm used in the zget task uses the statistics of the common overlap area While this should in theory produce good matching at the periphery of overlapped regions sometimes it is nece
20. nd image showing some of the dimples on the detector left panel These are not dead pixels and appear to divide out using a flatfield right panel to within 1 2 Figure 2 5 Line plot through one of the dimples left panel illustrating that they are smoothly varying regions of decreased response The same dimple after flatfielding shows that they divide out to within 1 2 right panel 2 4 1 3 Dead Pixels There are a number of unresponsive pixels in the array including one row 286 and one column 97 and several clumps which appear to be digs or scratches in the detector surface There are various techniques for making bad pixel maps described in the IRAF literature One technique which seems to identify most of the dead pixels is to divide two flatfield images at the same filter and integration times at two different signal levels either dome flats at different illumination levels or during a twilight sky flat sequence and use imreplace to set the pixels deviating from what should be a narrow distribution to the bad pixel value in the image Typically bad pixel maps utilize a value of 1 for bad pixels and 0 for good pixels WHIRC Data Reduction Manual Version 1 03 2009 August 24 10 In addition one can generate a bad pixel file which typically has a pl extension to identify specific pixels or regions which are bad Each line in the file identifies the limits of the bad region by the values x1 x2
21. rcsec Data reduction was done in the standard way The 100 frames were median combined to generate a sky frame which was subtracted from each of the input frames to yield the sky subtracted images Good quality dome flats in the J and Ks filters were obtained using the standard lights on lights off technique subtracted and then corrected for bad pixels using the fixpix task and the WHIRC bad pixel mask The flats were normalized using regions 400 600 400 1600 and 1400 1600 400 1600 which avoids the pupil ghost area and any other pixels of value lt 0 02 were set to 1 0 to avoid arithmetic blowup in the flattened images These flats which contain the pupil ghost are referred to as the uncorrected flats The template for removal of the pupil ghost was generated as follows e The normalized Ks and J band flats were ratioed to give a flat ratio image e Anew 2048 x 2048 image with pixel value 1 0 was generated with mkimage e The central 800 x 800 of the flat ratio image centered on the pupil ghost 625 1424 601 1400 was copied into the new image e The image was smoothed using the gauss task with sigma 31 e Subtract 1 0 from the result to yield the pupil ghost template image The uncorrected flats were run through the rmpupil task using the pupil ghost template image as the pupil and the pupil mask file pupmask pl as the pupilmask to restrict the procedure to the central 600 pixels 725 1324 725 1324 The param
22. s the detector in WHIRC is not perfect and has several types of cosmetic imperfections Some of these can be corrected to a degree during the data reduction 2 4 1 1 High Dark Current Pixels These are scattered throughout the array with certain areas such as the upper right having a higher concentration These show up as bright pixels particularly against a low background such as a dark or narrowband sky These pixels may also be characterized as maverick pixels since the signal is not necessarily proportional to the frame time as a true dark current would be The procedure of sky subtraction does seem to remove most of the elevated signal level although the noise in these pixels may be higher than in others Otherwise there is no remedy for these artifacts 2 4 1 2 Dimples A well illuminated image such as a flat Fig 2 3 shows numerous circular artifacts which appear to be dead pixels However closer inspection reveals that these are not dead but areas of decreased response which appear to flatfield out reasonably well Figs 2 4 2 5 The smooth variation evident in a cut through one of the dimples Fig 2 5 would make pixel correction algorithms such as fixpix based on nearest neighbor averaging problematic WHIRC Data Reduction Manual Version 1 03 2009 August 24 9 apm iE no mal Be ss a i ip ir E fa A id E Si oy np a a i onl z B Figure 2 4 Expanded subregion of H ba
23. sing the IRAF task apphot over a 10 x 10 raster centered on the WHIRC pupil ghost The magnitude scale is not calibrated to a photometric standard The same dataset is plotted for the sky subtracted unflattened data top panel data flattened with no correction for the pupil ghost middle panel and data flattened with correction for the pupil ghost bottom panel WHIRC Data Reduction Manual Version 1 03 2009 August 24 24 Flattened pupil correction 13 50 13 45 13 40 g 13 35 13 30 13 25 0 10 20 30 40 50 60 70 80 90 100 Number Figure 4 2 The pupil corrected flattened data from the lower panel of Fig 4 1 but plotted as a function of time in the order the data were obtained The line is a linear fit to the data and probably represents atmospheric extinction since the airmass increased over the span of the observations by approximately 0 20 WHIRC Data Reduction Manual Version 1 03 2009 August 24 25
24. ssary to tweak the levels in the individual images to get a better match Even with perfect matching of the intensity levels one can detect the overlap transitions because the noise will be lower in the central parts of the mosaic where more images were combined WHIRC Data Reduction Manual Version 1 03 2009 August 24 IS 500 1000 1500 2000 2500 3000 3500 4000 150 200 250 300 350 400 450 500 550 600 650 1000 1500 2000 2500 500 10001500 Figure 3 2 upper left Image of the M42 field in the narrowband H2 filter after trimming This is one of five images of the field taken in a plus pattern with 50 arcsec spacing upper right Sky image obtained by combining the five images of a nearby sparse field with a median filtering algorithm lower left Difference of the top two images Note that the sky subtraction reduces the residual background to near zero lower right After flatfielding the five images are combined into a single composite using the upsqiid package Note that the noise is higher in the periphery of the image where only a single image contributes to the mosaic This image is displayed using a logarithmic scaling to bring out faint details Observations courtesy M Meixner 3 3 1 Larger Mosaics Maps covering a larger area may be generated using the more generic IRAF tasks in the noao imred irred package In particular the tasks irmosaic iralign and irmatch2d can be used in a manner analogous to the upsqiid tasks noted a
25. sting several wavelengths are contributing most likely the strong OH Q branch lines in the H band Unfortunately unlike the pupil ghost the fringe patterns differ for each filter in both spacing wavelength dependent and phase In addition fringe patterns seen in a given filter appear to vary slightly in phase from one night to another Therefore one cannot use a generic template to attempt removal of the fringe pattern but must use the data from the same night Because the strength of the OH lines varies during the night fringes may not be seen in the sky frame see section 3 1 for any given target but they may very well appear in a supersky generated from all of the observations during a given night This is often the case in the H band in the PaB and Pa 45 filters the fringes will almost always be prominent since the continuum sky background is negligible and science exposures tend to be long The MOSAIC reduction task mscred rmfringe appears to do a credible job of removing these fringes from the sky frame As with the rmpupil task one needs a template of the pattern which will then be amplitude fitted to the fringes in the data and subtracted Since a generic template cannot be used one must generate the template from the science observations Refer to sections 3 1 and 3 2 following since the fringe removal will be carried out during these steps of the data reduction It is logical to apply the fringe removal to the sky s
26. system WIYN telescope WI TM and WHIRC was modeled using Zemax and optical distortion maps were generated in the J H and Ks filters These files were used as input to the RAF routine geomap to generate third order polynomial fits with an rms error 0 1 pixel The files whirc distort lt filter gt txt and whirc distort lt filter gt db produced by geomap can be downloaded from the WHIRC webpage and used in the routine geotran to produce distortion corrected images which can then be combined into a large mosaic with good registration to the edges of the field Fig 3 3 The chromatic effects on distortion are extremely small so the distortion files are almost identical NOTE Because geotran remaps each pixel slightly one should carry out the distortion correction on images which have already been processed by sky subtraction and flatfielding We have not investigated the effects of distortion correction on surface brightness measurements of extended sources The geotran routine should preserve flux when the fluxconserve flag is set to yes Until we gain more practical experience in quantitative evaluation we suggest that observers be conservative or at least cognizant of the potential effects of distortion correction on photometry Programs utilizing deep imaging of a small field using small dither amplitudes probably do not require correction Imaging over a more extended field even with small dither amplitudes may benefit from
27. ted for the input data inlist in the present case and the output data One may create an output list of the same length as the input list but with different image names such as a different extension to the name in which case one would enter the file name oultilist Alternatively one can enter an extension such as wp and the script will automatically create new output images with the basename extension appended It is possible to execute the task in place e g using inlist for both the input and output but this will lead to confusion with the unprocessed raw data backup which would have the same image names 5 5 Images which have been processed with wprep cl will have a keyword WPREP 1 added to the header so one can verify whether data have been processed 5 6 One can also quickly verify the process by comparing imstats of the raw and processed data The processed data will have fewer pixels 4194304 vs 4395200 and the maximum pixel value will be larger because of the linearity correction In addition data taken in Fowler 4 mode will be divided by 4 2 2 Generating Dome Flats It is generally a good idea to run imstat on the flats just to identify any possible bad frames and eliminate them from the input data 1 For each of the on off sets in the filters imcombine each set into a single image e g flat k on etc One can generally use average with avsigclip rejection although median should work as well For the l
28. ter of a standard star field had yielded The current experiment of measuring 100 positions over a 40 minute time frame does make assumptions about photometric stability over this time frame during a time of year not known for clear weather A plot of the data with time Fig 4 2 does appear to show some systematic variation as well as a slope which is probably a result of atmospheric extinction Az 0 2 during the sequence The p p scatter around a low order fit is 0 05 0 06 mag equivalent to an rms 0 015 mag An alternative approach is to image a field which is sufficiently crowded to spatially sample the area within and around the pupil ghost as this would not be sensitive to changes in sky transparency Unfortunately real life stellar fields of sufficient density are usually confusion limited with many fainter sources contributing a background which calls into question the photometric reliability of relatively coarse resolution surveys such as 2MASS WHIRC Data Reduction Manual Version 1 03 2009 August 24 23 Unflattened 13 50 13 45 13 40 Mag 13 35 13 30 13 25 0 100 200 300 400 500 600 Flattened no pupil correction 13 55 13 50 13 45 Mag 13 40 13 35 13 30 100 200 300 400 500 600 13 50 13 45 13 40 Mag 13 35 13 30 13 25 0 100 200 300 400 500 600 R pixels from ghost center Figure 4 1 Plots of the magnitude of a Ks 11 star measured in a 4 arcsec aperture u
29. ubtracted data since the sky subtraction may remove most 1f not all of the fringing and it 1s generally preferable to reduce any artifacts to the extent possible before applying additional reduction steps WHIRC Data Reduction Manual Version 1 03 2009 August 24 13 Generating the fringe template is similar to making a sky flat without the flat so one will require in addition to the science data a dome flat in the same filter and a series of darks taken at the same integration time as the science data 1 Create a sky image using imcombine on all of the images in a given filter on each target field with median filtering Since the sky level will probably be changing one should scale the image using the median value of a large subregion such as 500 1500 500 1500 Ideally this will result in a sky image from which all of the stars have been eliminated This may not work in extremely crowded fields For very crowded fields or those containing an extended source one should take dedicated sky observations see section 3 1 If one observed several fields through the filter at the same integration time one may generate a master sky image by imcombining all of these images this may enhance the fringe visibility as well as increasing the S N of the resulting frame The result will look something like Fig 2 8a 2 Average the dark frames as in making a sky flat section 2 3 and subtract from the average sky frame Fig 2 8b pe 4
30. y image using imcombe on all of the images in a given filter on each target field with median filtering as described in section 2 4 3 Since the sky level will probably be changing one should scale the image using the median value of a large subregion such as 500 1500 500 1500 Ideally this will result in a sky image from which all of the stars have been eliminated This may not work in extremely crowded fields For very crowded fields or those containing an extended source one should take dedicated sky observations see below 3 Inspect the sky image and if it looks OK generate sky subtracted images by subtracting the sky image from each of the original images If the sky level had changed during the observation series some of the sky levels may be positive some negative Keep going Fringe removal if necessary can be done at this stage 4 Divide each sky subtracted image by the flat for that filter This should result in images in which the non zero sky level is uniform across the image One can subtract WHIRC Data Reduction Manual Version 1 03 2009 August 24 16 this offset out by measuring the median level of the image and subtracting that number If one is doing aperture photometry the sky level should be automatically subtracted during that process 5 One may analyze the results from each image separately or combine them using upsqiid or other custom routines If making a large mosaic of images distortion correction may b
31. you will have a normalized flatfield for each of the filters WHIRC Data Reduction Manual Version 1 03 2009 August 24 7 Figure 2 3 Normalized flat for Ks left panel and J right panel The significant difference in the two emphasizes the need to obtain dedicated flats in each filter used for observing The pupil ghost in the J band is much less prominent but there is a noticeable fingerprint artifact probably resulting from a defect in the antireflection coating on the array Note that the bad column has been set to a value of 1 0 by imreplace 2 3 Generating Sky Flats We have not yet determined whether sky flats or dome flats are better for data reduction Except for the H and Ks bands though the nighttime sky flux is generally much too small to generate high S N flats We have generated J band twilight flats by taking a series of images once the sky level had fallen below the saturation level and combining them with scaling and a median algorithm much as is done in the visible In the Ks band thermal background from the telescope and WTTM optics will contribute to the background and the pupil ghost whereas the lights on lights off procedure for dome flats will subtract out this common signal Since sky flats can be generated from the target observations it is safer to get dome flats in any case 1 Sky flats are best generated from a series of observations which give an appreciable several thousand ADU sky level T
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