Analysis - Mullard Space Science Laboratory
Contents
1. Below the dotted lines and main cursor are printed the corresponding wavelengths for those points To move a ghost that has been identified position the cursor to the left of the ghost and press and drag the left mouse button over the ghost For instance to move the ghost previously identified at around 160A Section 4 2 2 press the mouse button with the cursor just to the left of 160A keep it depressed and move to about 162A see Figure 5 14 sBS25rO fits 1 1997 08 18 GIS1 S ee am umm ap A Hi coos Race right shifted spectrum SPECTRUM arb unite 160 170 180 180 Wavelength hngstrama 178 861 3B825r00 fita 1 1997 08 18 6151 loft shifted n P ee PEEL TER IT c M right shifted H Tnm JA p J AA AL PEN AM EE SPECTRUM arb unite 160 170 180 130 200 210 220 Wavelength ngetrama Figure 5 Manual relocation of ghosts using ghost_buster in automatic mode top the region around the ghosted line located at 160_ has been selected and bottom relocated to its parent line at 175 Let go of the mouse and enter r in the terminal window to move the line to the right Repeat this procedure until all the lines of interest have b2. each detector and for various high voltage settings are examined by the GIS team at MSSL and the best selected to produce the current set of GSETs The raw files associated with each GSET are also used to produce ghost information structures and files These enable likely ghosting regions to be identified and in many cases corrected for automatically see section 4 3 2 Finding GIS data The CDS mission dataset can be browsed interactively using the powerful widget based xcat routine IDL gt xcat qlds tstart tstart tend tend A lot of progress can be made using this routine such as displaying images and spectra It is a good idea to play with the menus at this stage if you haven t already done so For example try selecting GIS only from the Detector menu and put the required dates in the Start Time and Stop Time fields and try selecting each of the read file options It is also possible to investigate the databases directly using the list_exper routine This route is particularly useful when you want to find data automatically within one of your own IDL programs IDL gt LIST 18 00 21 Jan 1998 21 00 21 Jan 1998 OBS FOUND The output obs is an IDL structure which contains full details of the observations which CDS performed between the selected times You can get an idea of the contents by typing IDL gt help obs str You can use simple logic to select pa
3. GIS spectra gt bimage Return wavelength band integrated image gt spectrum Returns one dimensional spectrum at specified point gt windata Return block of detector data from one detector window gt windesc Return descriptor structure for one detector window integral calc To compute the atomic data integral for use in column or volume emission measure work mk cds map Make an image map from a CDS QL structure pix2wave Calculate CDS wavelength given a detector pixel location plot map Plot an image map readcdsfits Read and return the contents of a CDS FITS level 1 file show struct Display contents and breakdown of an IDL structure tftd Search for a string in header documentation utplot Plot X vs Y with Universal time labels on bottom X axis wave2pix Calculate detector pixel location given a CDS wavelength xcat widget interface to CDS AS RUN catalogue xcds snapshot Widget interface to CDS SNAPSHOT xdoc Front end to online documentation software 23 Appendix B Example Program Below is an example program that combines a series of exposures and plots the total spectrum The count rates within a section of the spectra are then plotted as an image pro example study detno laml lam2 study study filename string detno detector number from 1 to 4 laml lam2 wavelength range to integrate over in Angstroms e g to pick the 2
4. per pointing it takes about 15 seconds to transmit the data Thus to cover an area of 20 20 using the 4 4 slit and 50 second integration time per position takes just over 20 minutes Because the GIS electronic encoding is sensitive to the incoming count rate different GIS set up GSET parameters are needed for different expected count rates Much of this selection process is automated when the observation is uplinked to the spacecraft although the observer must specify the solar zone beforehand The zone is a rough description of the solar activity expected in the observation It can be one of e not on the solar disk The expected maximum detector count rates for these areas are below 5 counts second pixel quiet sun any quiet area of the sun including coronal holes The expected maximum count rates are 20 counts second pixel active region active regions including those on the limb The expected maximum count rates are above 20 counts second pixel Once the zone and other observation parameters raster size slit exposure time exact location etc are determined the CDS planner at the Experiment Operations Facility can insert the GIS observation into the current plan The combination of zone and slit selected will prompt the CDS planner to choose an appropriate GSET The GSETs themselves are pre determined from special raw observations made with the GIS A number of raw observations for each zone each slit
5. the following way IDL gt gis_utplot qlds qlds1 qlds2 qlds3 det_no lines lines gisfit gisfit Or alternatively a string array of program numbers for example IDL gt gis_utplot 26320 26322 26324 1 lines lines gisfit gisfit This will read correct calibrate and then plot the data In this case from a sit and stare observation which is displayed in Figure 6 The calibrated and fitted data is saved into the gisfit structure if this variable is passed on the command line If it already exists it is updated The gisfit structure can then be used to plot the corrected calibrated and fitted lines from the observations IDL gt gis_utplot gisfit Calling gis utplot in this fashion will result in a prompt for you to select a particular line from a list of available present in the structure to plot Alternatively the specific line id can be entered Ne VIII 770 e 8 5 09 00 12 20 15 00 18 00 21 00 00 00 Start Time 26 02 07 55 04 N Ill 764 2 0 T T T T T T L5 2 1 0 S 8 05 SC 0 0 4 1 4 1 1 4 09 00 12 20 15 00 18 00 21 00 00 06 Start Time 26 02 07 55 04 Figure 7 Output from gis_utplot for specific lines contained in the gisfit structure GIS specific software for determining temperatures emission measures densities and DEM s based on the output gisfit structure are under development T
6. 3 79 3 7 Fe XIV 220 08 2 6 Fe XIV 264 79 4 2 Fe XIV Si VII 274 20 5 7 Fe XV Al IX 284 16 22 3 Fe XIII 320 80 3 5 S XIV 417 60 3 9 Ne VII 465 22 4 4 GIS PRIME DENSITY SENSITIVE PAIRS IN GHOST FREE REGIONS Note the lines marked with n are NIS lines Ion Wavelengths Mg VII 280 74 278 40 XI 215 93 281 42 S XI 190 37 281 42 S XI 217 64 281 42 Fe XII 338 27 364 47n Fe XIII 202 04 200 02 Fe XIII 201 12 200 02 Fe XIII 202 04 203 79 Fe XIII 318 12 320 80 Fe XIII 320 80 348 18n Fe XIII 318 12 348 18n GIS GHOST FREE TEMPERATURE SENSITIVE LINE RATIOS Note that n is for NIS lines and s for SUMER lines Ion and Ratio Range of Sensitivity K V 172 17 629 73n 1 0 x 10 VI 173 1032s few x 10 VI 184 1032s few x 10 28 Ne V 416 20 569 20n 10 10 Ne V 416 20 572 20n 10 10 GHOST FREE LINES IN THE GIS RANGE SUITABLE FOR A DIFFERENTIAL EMISSION MEASURE ANALYSIS Ion Wavelength LogT K Ne VII 465 22 5 7 Ne VIII 780 30 5 8 Si VII 275 37 5 8 Si VIII 319 83 5 9 Si X 261 06 6 0 Fe VIII 168 18 5 6 Fe IX 171 07 6 0 Fe XI 188 22 6 1 Fe XIII 203 79 6 2 Fe XIV 220 08 6 3 Fe XVII 200 80 6 5 GHOST FREE GIS LINES SUITABLE FOR HIGH TEMPERATURE STUDIES Ion Wavelength A F
7. 77A line in detector 2 in study s7060r00 type IDL gt example s10716r00 2 276 278 erb mssl ucl ac uk 17 Feb 1999 Mee Ne Ne Ne Ne e print Reading study detector number print Plotting between wavelengths laml lam2 qlds readcdsfits study read in the qlds ghost buster glds ghost free areas gis calib qlds arcsec2 cm2 calibrate cds fill missing qlds guess missing data plot an average spectrum window 0 ghost_plot_one qlds detno angstroms Take a slice of the data M9 9 int spec gt bimage qlds lam2 xsolar xsolar ysolar ysolar Spec id GIS trim detno print Pixels chosen wave2pix spec id laml lam2 print Bottom left position on the sun min xsolar min ysolar plot the image M9 9 window 1 loadct 0 tvscl congrid int spec 512 512 return end 24 Appendix C Ghost free line lists Below are tables of expected count rates per second for lines for slit 1 2 x2 in ghost free areas in the four GIS detectors The lists are originally from the CDS Scientific Report Blue Book by Richard Harrison Tables 2 1 2 6 and 3 3 3 7 with lines in ghosted areas removed Note that this list is specifically for the ghost free areas of observations taken with GSET 41 quiet Sun 2 2 slit although the positions of ghosting are similar for all the GSETs A detaile
8. 8 0 Fe XII 338 26 1 2 4 2 Note that the He II and blended Si XI lines at 304 are not included because the intensity of these excessively bright lines cannot be calibrated DETECTOR 3 Ion Wavelength Quiet Sun Active Sun Intensity Intensity Ne V 416 20 0 2 0 8 Fe XV 417 26 1 1 34 6 S XIV 417 60 3 9 32 4 CIV CaX 419 50 419 74 0 7 3 0 26 Mg IX 438 60 0 2 0 8 Mg IX 444 03 0 4 2 8 Ca XV 445 00 0 0 3 6 S XIV 445 70 0 2 3 0 Si IX Mg VII 450 73 0 0 0 0 Ne VII 465 22 4 4 36 1 Ca IX 466 23 0 0 2 7 Ne IV 469 80 0 3 1 2 Ne M 489 50 0 2 1 2 Second order line blend DETECTOR 4 Ion Wavelength Quiet Sun Active Sun Intensity Intensity 685 83 1 1 2 2 C II 687 20 0 3 0 5 Ca IX 693 80 0 3 1 6 AI Ul 696 00 0 0 0 1 Mg IX NeI 735 90 0 4 2 6 OV 758 60 0 4 2 1 OV 759 44 0 0 0 0 OV 760 40 0 9 4 4 OV 762 00 0 0 0 0 764 00 0 0 0 0 Ne 780 30 1 4 16 1 S 782 00 0 0 0 2 783 00 0 2 0 7 Second order line blend BRIGHTEST GHOST FREE LINES VISIBLE WITH THE GIS The Si XI 303A and He II 304A line are not included because the intensity of these excessively bright lines cannot be calibrated Ion Wavelength A Quiet Sun Intensity counts second Fe IX 171 07 8 8 21 Fe XI 188 22 8 2 Fe XIII 20
9. CORONAL DIAGNOSTIC SPECTROMETER SOHO CDS SOFTWARE NOTE No 55 Version 5 August 2003 UCL SOHO CDS GIS Analysis Guide August 2003 Carl Foley Solar and Stellar Physics Group Mullard Space Science Laboratory University College London Holmbury St Mary Dorking Surrey RH5 6NT UK carl foley g mssl ucl ac uk Revision list Version 1 19 May 1999 Version 2 1 July 1999 Version 3 23 July 1999 Version 4 11 Jan 2000 Version 5 August 2003 Original Converted to CDS software note 55 Added approximate wavelength coverage added cross_cor keyword to ghost_plot_one described ghost_info added plot and hardcopy keywords to ghost_buster ghost_buster prints wavelengths with the ghost cursor added section on saving and restoring ghost sessions gis_calib uses new calibration coefficients described gis write calib added the new routines to Appendix A Expanded section on wavelength calibration Added automatic option to ghost buster and included associated ghost information structures Added flat field files and correction to gis calib Made photons sec arcsec cm2 default output from gis calib instead of counts Included error tag to the calibrated 4145 structure from gis calib Added new routine gis fit which corrects calibrates and fits the GIS data non interactively providing the user with a simple entry into the analysis of GIS data Included new gis utplot plot routine Restructured and worded analy
10. Using calibrated spectral datas ee eo a eae ite 19 6 1 Extracting the data from the qlds eese 19 62 TOC DLE DR e e ene NN Re E eet N E ts vend Shade Du as 20 6 3 GIS gir 21 EFGIS UTPLEO S va EI a 21 Appendix A List of 23 Appendix B Example ssec eia DW Lae cbt 24 Appendix C Ghost free line see eS eite vh e e rt aep P Ri tea med dia 25 1 Introduction The objective of this document is to guide the user into the use of data obtained with the Coronal Diagnostic Spectrometer s Grazing Incidence detector GIS which is part of the SOHO payload This document should be used in combination with the instrument guide which contains more detailed information with regard to the detectors and their in flight characteristics It is recommended that the instrument guide is read first and then the analysis process described here followed Reading and calibrating the GIS data is simplified greatly by using the Solarsoft IDL library which is maintained and distributed at Lockheed Martin http www lmsal com solarsoft It is also available at the Solar UK research Facility at MSSL http surfwww mssl ucl ac uk solarsoft where full instructions and support for the installation and maintenance of the software is available Some familiarity with the IDL analysis package is assumed and Solarsoft is assumed To make the CDS l
11. bles waverange can be used to limit the fit to a particular line and is the polynomial order of the background Thus to fit a Gaussian plus background to a region in the first exposure of the above GIS detector 3 data IDL gt wavescale pix2wave GIS3 indgen 2048 IDL gt data GIS3data 0 0 0 IDL gt waverange 415 420 IDL gt ezfit wavescale data waverange k 1 Another routine cds gauss has been developed for use with CDS data yfit eds gauss x y a Where x 1s the independent vector y 1s dependent variable a contains the returned coefficients and defines the order of the polynomial to be fitted to the background A more complicated but very comprehensive fitting routine is cfit yfit cfit x y a fit sigmaa keywords Where x y are the data to be fitted is an array of nominal parameter values if defined then used as an initial guess to the fit fit is a structure containing one tag for each component in the fit sigma contains the errors for each of the parameter values ina For detailed information about c it see CDS software note 47 The Component Fitting System for IDL 20 63 GIS FIT GIS FIT uses predefined cfit structures to automatically fit most regions of the GIS spectra IDL gt gisfit gis fit qlds plot gisfit gisfit This routine works on calibrated and uncalibrated data Un calibrated data is corrected and calibrated automatically using the individual routin
12. d check of ghosting in an observation can be made with ghost_plot_one qlds detno DETECTOR 1 Ion Wavelength A Quiet Sun Intensity Ni XIV 164 13 0 4 Ar X 165 49 0 0 Fe VIII 167 168 2 0 Ni XIV 169 68 0 0 Fe IX 171 07 8 8 OV 172 17 0 1 O VI 172 93 173 08 0 7 O VI 183 94 184 11 0 4 Fe X 184 54 22 Fe XI 184 79 0 2 Fe VIII Ni XVI 185 22 0 8 Fe VIII 186 60 0 5 Fe XII 186 88 2 4 Fe VIII 187 23 0 0 Fe XI 188 22 8 2 S XI 188 67 0 3 FeX 190 04 1 3 Fe 191 26 0 3 Fe XIII 200 02 0 7 Fe XII XIII 201 12 2 0 Fe XIII 202 04 0 9 S VIII 202 61 0 4 Fe XIII 203 79 3 7 Fe XIII 204 26 0 0 Fe XIII 204 94 0 6 SX 208 32 0 0 Fe XIII 208 68 0 0 Fe XIII 209 62 0 0 25 Si VIII Si XII 214 76 215 15 0 8 Si VIII 216 90 0 6 Fe XII 217 27 0 0 5 XII 218 18 0 4 Fe XIV 219 12 2 0 Fe XIV 220 08 2 6 DETECTOR 2 Ion Wavelength Quiet Sun Active Sun Intensity Intensity Si X 261 06 1 5 Fe XVI 262 98 L3 Fe XIV 274 20 5 7 Si VII 275 37 275 76 0 5 Mg VII 276 15 0 2 Si VII Si VII 276 77 276 85 0 2 Mg VII Si X 277 04 277 27 2 3 Mg VII Si VII 278 40 0 5 XI 281 42 0 5 S XI 281 83 0 0 S XII 299 50 0 2 Fe XI 308 54 0 0 0 0 Fe XIII 318 14 0 9 29 Si VIII 319 83 1 3 2 5 Fe XIII 320 80 3 5 11 5 Fe XV 321 78 2 3 7 9 Fe XV 327 02 2 4
13. e XXIII 154 27 Fe XXIII 166 74 Fe XXIII 173 31 Fe XXIV 192 02 Fe XXIII 263 76 Fe XXII 217 30 29
14. een corrected When moving a ghost remember to include enough background for line fitting on either side of the line of interest It is possible to restore more ghosts by running the program again on the same detector or any other Use the plot or hardcopy keywords to see the final result alternatively use gis plot or ghost plot one when finished 4 3 3 Saving and restoring ghost buster sessions By adding the save save struct keyword it is possible to save the ghost corrections made in manual mode into an IDL structure variable It is then possible to restore these corrections to uncorrected data with ghost buster qlds detno restore save struct plot hardcopy For example 15 IDL gt ghost_buster qlds1 1 save save struct IDL gt save save struct filename glds1 detl save and then at a later time IDL gt restore qlds1_detl save IDL gt ghost_buster qlds2 1 restore save_struct The first call to ghost_buster is in manual mode and the software will prompt for corrections to the data as outlined above The corrections are stored in an IDL save file The second call uses the restored information to reapply the corrections to a second data set Note that both 1981 and qlds2 must use the same GSET and that the same detector number in this case must be used 4 4 Edge effects Most detectors show edge effects both as spikes and a gradual increase in the background There are many causes for these
15. effects notably a compression of the wavelength scale causing an increase in the background end spoiling in the microchannel plates where the strong electric fields diverge at the ends of the detectors changes in the solar background mainly from the Hell continuum and some very bright solar lines seen especially in detector 2 Preliminary corrections for the non solar sources are now included in gis calib These have relatively large errors associated with them which are passed into the output structure These will reduce as we acquire more observations to check the corrections S Calibrating GIS Data The GIS calibration has recently been updated using the results of workshops which were held at the International Space Science Institute ISSI during 2001 These workshops were used to determine using intercalibration observations to find an absolute and relative intensity calibration for all the instruments on SOHO This resulted in an overall upward shift in the sensitivity of the GIS by 2 6 More recently it has been found that the lines in GIS 1 and 2 were becoming degraded due to the effects of Long term gain depression For this reason new flat field files have been generated to correct for this degradation Because of the size of the corrections as much as 60 and associated uncertainty a pixel by pixel error array is now included in the calibrated qlds structure This can be extracted using the gis error function IDL gt
16. error gis_error qlds detno 16 5 1 Wavelength Calibration Wavelength calibrations are read in automatically when the fits file is converted to a qlds The wavelength calibration can be accessed by the routines wave2pix pix2wave which translate the GIS pixel co ordinates as necessary pixel wave2pix spec_id wavelength limit Where for the GIS spec id is string containing GIS1 6152 6153 or wavelength can be a single value or an array See the example program B Similarly wavelength pix2wave spec_id pixel Which will return the wavelengths of the pixel array for the spectrum Again the input can be a single value or an array Variations of about 20 of a line width are expected between observations caused mainly by GIS hardware temperature differences when observing different areas of the sun or very high count rates more than about 40 counts second pixel causing distortions in the electronic processing Note that the wavelength calibration varies with each GIS setup GSET compare two GIS observations that used different GSETs it is necessary wavelength calibration This is simplified with the routine restore_wavecal For instance below is part of an IDL session to over plot two GIS observations IDL gt glds 1 readcdsfits s8965r00 IDL gt qlds_2 readcdsfits s8966r00 IDL gt gis smooth 4145 1 IDL gt gis smooth 4105 2 IDL gt print restore wavecal glds 1 prints 1 If restored IDL gt wave 1 p
17. es described in the previous sections of the analysis guide Gis smooth Ghost buster gis calib etc The visible identified lines are then fitted using the efit line fitting routine The output structure contains the fitted line positions widths intensities errors and total line counts in photons sec arcsec along with ancillary data such as the location and time of observation The gisfit structure can be used to quickly produce light curves images and DEM maps 64 GIS UTPLOT To display a quick time series of data acquired with GIS you can use the routine gis utplot This is a wrapper to the Solarsoft utplot program which displays a time series of the data acquired To call IDL gt gis utplot 4145 det no uttime uttime gisfit gisfit This plots a time series of the raw accumulated counts for the selected detector see Figure 6 GIS 1 Average Detector Rates 1 2 104 1 0x10 B Ox10 6 0x10 40x10 2 0x107 09 00 12 00 15 00 18 00 21 00 00 09 Start Time 26 02 07 55 04 Figure 6 The output from gis_utplot for a series of sit and stare observations in an active region located at the limb Note the dimming periods around 17 00 and 20 00 UT This is investigated in Figure 7 where individual lines are plotted 21 This routine also works with arrays of 4145 structures So if you have a series of 4145 from a particular observation you can combine these in
18. first notice that it is a clear area of the plot 1 e not in a ghosting area Neither the left nor right shifted spectra show lines at this point and thus this line is free from ghosts 4 2 3 Ghost Information files and structures The ghost information files contain the pixel locations of ghosting regions which aren t corrected for automatically by ghost buster All GSETS have a ghost information file which is stored with the other GIS calibration files located in the SCDS GIS CAL INT directory Also located in this directory are the ghost information structures which are used by ghost buster to automatically restore ghosts 12 4 3 Ghost Correction There are now three modes for ghost correction automatic manual and ghost free By default ghost_buster works in automatic mode This automatically corrects for most ghosts where they are not coincident on other lines and are resolvable IDL gt ghost_buster qlds plot hardcopy nm This corrects for about half of the ghosts or 70 of the data see Figure 4 2500 2500 rmm 2000 1500 8 ol o 5 5 1000 500 al 160 170 180 190 200 210 226 160 170 180 190 200 210 226 Wavelength A Wavelength A Figure 4 Ghost buster automatic restoration of ghosts Left uncorrected averaged smoothed spectrum right The same spectrum corrected using ghost buster in automatic mode This works well for quiet sun observations restoring almost all
19. hat show very little less than about 5 or no ghosting IDL gt ghost_buster qlds free plot hardcopy nm About half of each spectrum is returned Ghost free mode is available for all GSETs Use the plot or hardcopy switches to see the changes applied to the qlds After using ghost free mode blocks of data from the known ghosting regions will be missing from the qlds The areas remaining can be used without needing ghost correction 4 3 2 Manual mode Manual mode allows the user to move ghosted lines within a single detector To run in manual mode supply two parameters the qlds and a detector number IDL gt ghost_buster qlds detector_no hardcopy nm sample logscale plot angstroms save save_ struct Manual mode allows the user to specify which GIS spectral lines to relocate The program gives hints by using ghost_plot_one Section 4 2 1 to show the spectrum with overlying spectra shifted both to the left and to the right a cross correlation with these spectra and an estimate of the amount of ghosting in each direction It also uses a ghost cursor to show exactly where a spectral line would ghost The main cursor is a solid vertical line either side of it is a dotted ghost cursor The dotted lines are where any selected data will be moved to i e they correspond to the next or previous spiral arms The spacing between the dotted lines and the main cursor vary across the spectrum as do the shifted spectra
20. ibraries available on unix platforms and invoke IDL within SolarSoft use the system commands setssw cds sswidl If using the CDS operations version of the IDL software available from the Rutherford Appleton Laboratory then try the system command cidl though this may vary at different sites Many routines are available within the CDS SolarSoft library some useful ones are summarized in Appendix A To find which routines which are available for a particular task use the IDL command s enclose optional inputs IDL gt tftd search_string lines lines prog cat cat This searches the CDS SolarSoft IDL directories for all occurrences of the search word in routine descriptions For more information about individual routines read the routine header documentation with xdoc routine or doc_library routine_name In the following sections we describe the analysis techniques which may be used with the GIS data It is recommended that the doc_library routine is used to investigate each of these routines further since the headers contain a lot more information and available options which are omitted here for clarity 11 Related Documents The GIS software forms part of the CDS SolarSoft package put together at RAL Oslo Goddard MSSL and other places The associated CDS Software notes are particularly useful and they come as part of the CDS SolarSoft program library distribution A few of them are li
21. ill reduce the fixed patterning seen in the figure but increase the line widths somewhat the increase depending on the size of the boxcar used Thus instead a convolution with a Hanning function is used in the program gis smooth This function preserves the total counts in the spectral lines without introducing artifacts in the background or increasing the line widths s10716r00 fits SPECT_1 1998 03 26 GIS1 8 6 Counts exposure EN T Smoothed counts per pixel exposure per p P 0 186 187 188 189 190 186 187 188 189 190 Wavelength Angstroms Figure 2 A plot of the data around an Fe XI line from study 10716 showing fixed patterning left plot where data shows large variations from pixel to pixel The right plot shows the same data after running gis smooth To smooth the data within a qlds use IDL gt gis_smooth qlds smoothsize size The option smoothsize exists to change the size of the function used but the default smoothsize 7 works under normal circumstances To assist with the smoothing operation any missing data in the data set are estimated automatically the smooth function is applied and then the original missing data marked as missing again It is not recommended to replace missing GIS data separately before using any of the GIS processing software it is taken into account already by the programs 4 2 Ghosts An effect in the GIS detectors is the presence of ghosts These are displaced spect
22. ix2wave GISI findgen 2048 IDL gt data 1 gt windata glds 1 0 window 0 is for detector 1 IDL gt print restore wavecal glds 2 IDL gt wave 2 pix2wave GIST findgen 2048 IDL gt data 2 gt windata qlds 2 0 window 0 is for detector 1 IDL gt plot wave 1 data l max data 1 xrange 187 190 psym 10 IDL gt oplot wave 2 data 2 max data 2 5 2 Intensity Calibration As well as the ghosts and fixed patterning the detectors and their electronics have non linearities that need to be corrected On the whole these corrections are small less than 10 but dependent on count rate gis calib will correct for these as well as correct for gain depression and calibrate from counts into photons using the updated GIS calibration coefficients gis calib qlds errmsg errmsg quiet steradian m2 counts 17 By default the data will be returned in calibrated units of convert to photons per second per solid angle per area use the steradian m2 or to leave in counts counts switches The routine checks to make sure the routine ghost buster has been run for all the detectors if not the error for data in the regions likely to ghost is set to 10096 of the counts in the adjacent arms Similarly the error for regions which cannot be calibrated for any other reason is also set this might include the occasional strong line that is too bright for the gain depression calibration such a
23. lines To correct the remaining ghosts where the ghost lands in the location of another line manual mode is required This is described below However if from using ghost plot one the region of interest does not need correcting then use ghost free mode Once the ghosted areas have been removed with this mode then the data can be further calibrated without problems If the region does need correcting then run in manual mode Care must be taken with manually corrected data it is possible to run ghost buster without making any changes yet the software still allows further calibration Because the corrected count rates must be used for the count rate dependant gain depression calibration see below it is important to replace the ghosts in any region of interest before calibrating further Only ghosts of the lines within the region of interest need to be moved all others can remain in place without affecting the calibration If spectral lines need to be fitted it is recommended to correct for ghosts first calibrate the data and then fit the lines In either mode it is possible to run ghost buster again in the same or a different mode although if it is run on the same detector a warning will be 13 displayed To reset all spectra to the uncorrected state it is necessary to re read the qlds from the data file 4 3 1 Ghost free mode This mode uses the ghost information files section 4 2 3 to return only those areas of the GIS spectra t
24. marked as uncalibratable e Long term gain depression and flat field The correction is based on the total accumulated charge extracted from the MCP s Detector grating telescope effective area The calculations are based on a ground based calibration exercise for the whole of CDS The relative calibration coefficients have since been verified in flight but please note that there is currently a very large uncertainty in the absolute values 18 6 Using calibrated spectral data Various CDS and other SolarSoft routines exist to use the data once calibrated most of these can be used with both NIS and GIS data The generic dsp menu program will work with both calibrated and un calibrated data dsp_menu qlds qlds2 qlds3 delete nocheck 6 1 Extracting the data from the qlds To extract the spectral data from a qlds always use gt_windata or gt_spectrum data gt_windata qlds window nocheck quick nocopy nopadding errmsg errmsg These routines will work with all storage schemes used for CDS qlds data With GIS data specify the qlds and the window which is one less than the detector number For example to extract detector 3 data from a pre defined qlds use IDL gt GIS3data gt_windata qlds 2 The returned data are a floating point array of up to 4 dimensions spectrum always 2048 pixels for the GIS solar x solar y and time The time dimension is only used for data that have multiple exposu
25. o find the latest routines browse using IDL gt doc_library gis 22 Appendix A List of useful routines Some useful CDS and other SolarSoft routines along with one line descriptions For detailed information examine the routine headers with xdoc routine name cds fill missing Fills MISSING pixels in QLDS cds gauss Fits Gaussian with constant linear or quadratic background cds snapshot Makes a thumbnail sketch of images from a CDS study chianti ne Calculate and plot CHIANTI density sensitive line ratios chianti ss Calculates and plots CHIANTI synthetic spectrum chianti te Calculate and plot CHIANTI temperature sensitive line ratios cfit Make a best fit of the sum of components to the supplied data dsp menu Selection of display modes for CDS QL data Ezfit Easy Gauss fit to data Ghost buster Move GIS detector ghosts Ghost info Display the ghosting information associated with a QLDS Ghost plot all Plots all 4 GIS detector data with likely ghost regions Ghost plot sample Plots or returns a theoretical sample GIS spectrum Ghost plot one Plots a GIS detector data with likely ghost regions gis calib Applies calibration factors to GIS spectra gis plot Summarise data from one GIS detector gis smooth Smoothes GIS spectra to remove fixed patterning gis write calib Prints calibration factors for
26. only a guide to where ghosts may be located and is easily confused by line blends By default the correlation is not plotted To summarise the data from all four detectors in a similar way use IDL gt ghost plot all qlds angstroms nm 4 2 2 Finding Ghosts The output from ghost plot one Figure 3 can be used to check whether a line is ghosted or itself is a ghost Suppose we have seen a line and want to check it for example there is a spectral line on the plot between 160 and 161 these ghosts are now corrected automatically by default since they are located in non blending regions see section 4 3 This line is in the ghosting region defined by the shaded region on the plot The first check is to look at the theoretical quiet sun spectrum it shows that there are no lines at this location This may be a fault with the theory however further checking shows that the left shifted spectrum also has a line at this point This strongly suggests that the line at about 160 is a ghost and needs to be pushed to the right to correct the line The manual ghost correction software explains the process of moving the line in more detail as well as overlaying a ghost cursor on the plot This cursor shows exactly where lines would come from if they are ghosts Alternatively if we are familiar with this area on the solar spectrum we know there is a FeXIII line at 202 see Appendix C To see whether this line needs correcting
27. ral lines or parts thereof caused by an ambiguity in the encoding used by the electronics The routine ghost_buster is used to remove or return ghosts in the GIS data When the GIS is in raw data mode it transmits the data from one detector as a series of coordinate pairs from the detectors When these coordinates are plotted they form a spiral see the GIS Instrument Guide where the spectral dimension lies along the length of the spiral and the intensity is the number of counts at each position along the spiral To translate these pairs into spectral position a Look up Table LUT is used as part of the on board GIS processing The parameters that define the LUT plus the high voltage setting form the GSET mentioned earlier Every GSET includes a different set of LUT parameters and the LUTs are calculated by the on board GIS processor for each detector immediately before the first observation using that GSET The ambiguity or ghosting in spectral data does not occur over the whole spectral range but where the thin spiral arms broaden and overlap each other If a spectral line is ghosted it is confined to occur only at specific locations in adjacent spiral arms These characteristics are used in ghost_buster to restore the ghosts to their original locations The counts in a ghost must be added to the counts at the original location to produce the correct line intensity In ghosted areas which cover 40 to 50 of the data it is easier to sepa
28. rate the original line from ghosts where there are no blends Thus ghosted areas in quiet sun observations are easier to correct than in an active region although the unghosted areas remain unaffected for all observation zones 4 2 1 Displaying GIS Ghost details The output from ghost_plot_one e g Figure 3 displays the GIS data with an emphasis on sorting ghosts from the original data ghost_plot_one qlds detector_no sample nm angstroms logscale pixels waverange min max cross_cor This routine allows switches to modify how the data are plotted For instance waverange can be used to zoom into a particular region of interest by specifying a minimum and maximum wavelength to be plotted and sample plots a sample theoretical spectrum The routine first adds all the data from an observation into one spectrum per detector then plots the data with information to help find possible ghosts Figure 3 was produced using IDL gt qlds readedsfits s10716r00 IDL gt gis smooth qlds IDL gt ghost_plot_one qlds 1 sample angstroms 10 10716r00 fits SPECT_1 1998 05 26 GIS1 theoretical quiet Sun spectrum left shifted spectrum right shifted spectrum SPECTRUM arb units 180 170 180 190 200 210 220 Wovelength Angstroms Figure 3 output from ghost plot one top top theoretical quiet sun spectrum top middle left shifted spectrum top bottom right shifted spectrum Bottom Spectr
29. res at the same solar x y point To get information about the extracted data use gt windesc glds window nocheck quick errmsg For example IDL gt GIS3desc gt_windesc qlds 2 The returned structure tells us which units the data use GIS3desc units the missing data flag G1S3desc missing the wavelength range GIS3desc wavemin GIS3desc wavemax etc The command IDL gt xshow struct GIS3desc will display all the information available in the structure Also available is gt spectrum to get individual spectra from a raster result gt spectrum glds window window yix yix tix tix lambda lambda xsolar xsolar ysolar ysolar time time Where window yix xix tix are the user supplied window 1 6 the detector number 1 and for each raster position the x y and time indices The time index is not normally used unless the raster has repeated exposures at the same position If supplied lambda will return the wavelength for each pixel in the spectrum xsolar and ysolar 19 are the locations on the sun in arc seconds from the sun centre and time is the time of the start of the exposure 6 2 Line fitting Many fitting procedures are available see tftd gauss andtftd voigt which can be used to fit various profiles and backgrounds to ghost free or ghost corrected GIS spectra One of these is ez it ezfit wavescale data waverange k k where wavescale and data are the X and Y varia
30. rticular observations For example to select all the GIS observations performed in the selected time interval IDL gt gis where OBS detector eq G IDL gt print OBS filename gis 3 Reading and displaying GIS data The SOHO CDS data are stored and distributed in FITS format which can be read into a quick look data structure qlds using the readcdsfits routine For example to read in the GIS data set defined as study number 54384 raster r00 IDL gt qlds readcdsfits s4384r00 The qlds contains the spectral data some wavelength calibration information ancillary information about spacecraft pointing and much more in a hierarchal structure similar to that obtained using the LIST EXPER routine mentioned in the previous section It is possible to browse all the information in the qlds with the following IDL gt help qlds str This will display the following QL_ID DOUBLE 1 0570199 009 NO INT 1 HDRTEXT STRING 481 HEADER STRUCT gt HDRX Array 1 DETDESC STRUCT gt GISXX3 Array 4 BACKGROUND INT 0 WAVECAL STRUCT gt GIS_WAVECAL Array 1 DEL TIMEDATA DOUBLE Array 20 DEL TIMEDESC STRUCT gt AUX2 Array 1 INS FLOAT Array 20 INS XDESC STRUCT gt AUX2 Array 1 INS YDATA FLOAT Array 20 INS YDESC STRUCT gt AUX2 Array 1 The structure can be investigated further in the following fashion IDL gt help glds header gset id This will display the GSET for thi
31. s observation This embedding of information with the data is a powerful method of distributing the data and greatly simplifies the analysis process making easy to quickly display and analyse the raw data For example to plot all four GIS data windows you can use the routine cds_ snapshot IDL gt eds snapshot qlds spectra log window window Broadband GIS 1 Broadband GIS 2 1000 00 1 008 00 100 00 1008 00 100 00 16 sei 16 60 1 00 1 00 Q 10 G 10 2 01 2 01 166 170 180 130 200 210 250 280 300 320 Broadband GIS 3 Broadband GIS 4 1006 00 106 60 100 00 10 00 10 00 1 00 1 00 0 10 Q 10 Q 01 Q 01 400 420 440 460 480 660 680 700 720 740 766 SOHO CDS GIS Raster 25 1996 15 13 16 G24L Activity Boundary s4384r00 fits Center 279 72 Size 8154 Figure 1 cds_snapshot of GIS data using the log switch The salt and pepper noise which can be seen over this data is due to fixed patterning described in section 4 1 This plot displays spectra since the G2AL study is a sit and stare study For rasters snapshot will display an image unless the spectra switch is used 4 Correcting GIS Data for Instrument Effects 4 1 Fixed Patterning Fixed patterning is an effect caused by the interaction of the GIS digital electronics with the analogue detector read outs it is very pronounced in some parts of the GIS spectra Figure 2 shows a subset of data from detector 1 A boxcar smooth of the data w
32. s the Hell 304A line or whole detector count rates too high for the electronic dead time corrections The GIS calibration coefficients used are those from the results of the SOHO radiometric inter calibration workshops which were held at the International Space Science Institute ISSI during 2001 The coefficients can be viewed using the program gis write calib 5 2 1 Calibration details The corrections and calibrations made by gis calib include e FIFO dead time The dead time is a straightforward correction for an on board First in First out FIFO event queuing chip It applies to all four detectors simultaneously and involves a constant non extending dead time allowing 10 counts per second through unhindered with small corrections for higher rates Simple correction for Quiz show dead time The programmed Quiz show correction is simply an upper limit on the rates if photon events are less than 6 microseconds apart then the data are marked as uncalibratable The maximum rate is then 1 0 6 0 105 or approximately 1 7 10 over all four detectors e Analogue dead time This involves an extending dead time of approximately 2 microseconds The data used to correct for this were measured before launch using the flight electronics and are read from a data file Count rate dependant gain depression also known as short term gain depression If more than 5 error would occur in the measured rates then the datum at that point only is
33. sis guide throughout Put on web in HTML format with example programs etc Table of contents au Sal cote etes tea a ha la ied 4 1 1 Related Documents we desert rite eter e ev ied Pera 5 1 2 GIS ObSGFUALIOBS quie E 5 2 Finding GIS usn Reel aas 6 2 1 Browsing the CDS Catalogue eite bend oe n cde bog e 6 3 Reading and displaying GIS a Reus 7 4 Correcting GIS Data for Instrument Effects 8 T L EixedPattetmifgus o sos va e aee o 9 m em cn su S E 10 4 2 1 Displaying GIS Ghost details tem ect etn ente seti ttn 10 En pi Iesu Pe a NOR Pope t ed V dde 10 4 2 3 Ghost Information TUS oen c RD p ub 12 4 3 GhlostC Seco en item erste e orbi pe oe EE HER 13 4 3 AU Ghost abo tear td 13 4 3 2 Man al mode 14 4 3 3 Saving and restoring ghost buster 8851018 15 4A Edge effects eost e a Neuen ttu dac S 16 5 Calibrating GIS Data ie Asada Gre Dabei uten o Der eb er D SO e al ERO E ede Ales 16 5 1 WavelehpthiCablibratiotizs oio d e doa deti i e ee a ada tet inus 17 5 2 Intensity Calibr tion pose eti rq OPER RD e ie aes Uer te rd tr epe 17 5 21 Calibration Cle tall Se a ak ute eon 18 6
34. sted below all the notes can be obtained from the web at http orpheus nascom nasa gov cds software notes html CDS software note 54 The GIS Instrument Guide a detailed description of the GIS instrument CDS software note 20 CDS Quicklook Software User Manual is an introduction to the general CDS software available CDS software note 22 CDS on line help utilities To find your way about the IDL software in the CDS SolarSoft distribution CDS software note 9 The CDS Quicklook Data Structure Gives more information about the quick look data structure qlds and the data within it CDS software note 47 The Component Fitting System for IDL For fitting Gaussians Voigt profiles etc to spectra CDS software note 37 Diagnostic Line Ratios using CHIANTI for CDS Using the CHIANTI atomic physics databases with CDS data CDS software note 33 The CHIANTI Synthetic Spectrum Program for CDS SUMER CDS software note 50 Differential Emission Measure analysis using CHIANTI 1 3 GIS Observations Unlike the NIS observations with the GIS are astigmatic and the whole of the spectrometer slit is used to produce the spectra To cover an area larger than the normal GIS slits 2 2 4 4 and for observations away from the solar disc 8 50 the scan mirror and slit are moved over an area of up to 4 arc minutes Data from all four detectors are gathered simultaneously and although the minimum integration time is 1 second
35. um to be de ghosted with likely ghosting regions shaded The areas of the resulting plot are described from the top Theoretical quiet sun spectrum This is the spectrum requested with the sample keyword There are a number of warnings that come with the sample spectrum See xdoc ghost plot sample for details The spectrum is intended only as an aid to ghost restoration the intensities of lines are only approximate e left shifted spectrum and correlation The spectrum plotted is a copy of the observed data but shifted to the left by one spiral arm Any ghost that occurs can only be from an original line one arm to the left or to the right As the ghosting scale is not linear the amount of shift varies across the detector e shifted spectrum a copy of the observed data shifted to the right with the optional correlation e SPECTRUM The lower part of the plot contains a summary of the data where all the exposures in the observation have been added together The grey boxes underlying the plot are information from ghost information files which show where the ghosts are expected The vertical scale is in arbitrary units to show 11 most of the lines but to enhance the weaker lines plot logarithmically with logscale If the cross_cor keyword is used the correlation between the original and shifted spectra is displayed If the absolute cross correlation coefficient is greater than 50 it plots a thick bar This is
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