Using MARX to Simulate an Existing Observation
CIAO 4.16 Science Threads
Overview
Synopsis:
Simulating rays with MARX is very similar to the steps needed to reproject ChaRT rays, and is only a matter of setting a couple additional parameters. The MARX software is used to generate and project the rays onto the detector plane.
Note that MARX was originally intended as a PSF simulator and not an observation simulator.
Using MARX allows the user to take into account all changes to the photon distribution emerging from the HRMA due to the detector response. In particular, the detector QE & QEU and the roll are accounted for. In addition to simulating the detector response, MARX uses the ray weights to account for the mirror effects, i.e. different efficiency of different shells at different angles/energies.
Related Links:
-
The full MARX documentation and more examples can be found at https://space.mit.edu/cxc/marx/.
- Caveats page: details on what is not included when using MARX.
- The MARX Frequently Asked Questions webpage
- Using a PSF Image as the Convolution Kernel
Last Update: 23 Oct 2024 - revised and simplified Python/NumPy filtering syntax in input spectrum restrictions admonition.
Contents
- Get Started
- Setting up MARX
- Simulating the Source
- Create an Events File
- Sub-pixel Analysis
- Encircled Counts Fraction
- Summary
- History
- Images
Get Started
This example uses the point source spectrum of τ Canis Majoris—an eclipsing spectroscopic binary, which is extracted near the detector's aimpoint for an observation of the open cluster, NGC 2362—and used to simulate a point spread function for this particular observation.
Download the sample data: 4469 (ACIS-I, NGC 2362)
unix% download_chandra_obsid 4469
Re-process it with chandra_repro:
unix% cd 4469 unix% chandra_repro . repro/ check_vf_pha=yes
The files we are going to use are in the repro/ directory, shown in bold (note that only the events file needs to be explicitly specified since the remaining files can be found automatically by specextract).
unix% cd repro/ unix% ls
In order to simulate a PSF of the point source, a distribution of incoming photons is needed to interact with the telescope's optics before being projected on to a detector. Generally, when simulating a PSF for an observation, the incident source spectrum should be background subtracted. τ Canis Majoris' coordinates are RA=07:18:42.457 [109.6769 deg], Dec=-24:57:15.78 [-24.954383 deg], and specextract is used to extract the source spectrum in a circular region; a background with an annulus; and calculate unweighted response functions. Since the background will not be modeled, responses for the background need not be made.
unix% specextract \ infile=acisf04469_repro_evt2.fits"[sky=circle(07:18:42.457,-24:57:15.78,0.0666667')]" \ outroot=4469 \ bkgfile=acisf04469_repro_evt2.fits"[sky=annulus(7:18:42.457,-24:57:15.78,0.0666667',0.15')]" \ bkgresp=no weight=no correctpsf=yes grouptype=NONE verbose=0 mode=h unix% ls spec 4469.arf 4469_bkg.pi 4469.corr.arf 4469.pi 4469.rmf
MARX requires the spectrum to be in units of flux density, photon/s/cm2/keV, input as an ASCII table with the first column as energies in keV and flux densities in the second column. The observed spectrum is mapped from channel- to energy-space by the RMF, with the units as counts instead of photons. To analytically obtain the "true" source spectrum—which will be in photon units—requires deconvolving the responses from the observed spectrum. Numerically, this can be done by dividing the observed spectrum by the detector responses. In Sherpa, the plot_ratio command—which divides the observed spectrum with a model spectrum, the model spectrum being a source spectrum convolved with the ARF and RMF—using a constant source model set to unity, so that the model spectrum is a discrete representation of just the detector responses, may be used for this purpose.
sherpa> load_data("4469.pi") sherpa> subtract() sherpa> notice("0.3:11.0") sherpa> set_source(polynom1d.truespec) sherpa> truespec.c0 = 1 sherpa> photonflux = get_ratio_plot().y # ph/s/cm**2/keV sherpa> energy = get_ratio_plot().x # keV sherpa> photonflux[photonflux < 0] = 0 # replace negative fluxes, from background subtraction, with zeroes sherpa> save_arrays("tCanMaj.dat",[energy,photonflux],["keV","ph_s_cm2_keV"],ascii=True)
The save_arrays command writes the energy and photonflux arrays between ~0.3-11 keV, rounded to the closest energy bin, to the ASCII file tCanMaj.dat.
Setting up MARX
This thread uses MARX v5.5.3; if you do not already have the software, download and install MARX before continuing. The install_marx script may also be used to download and install the lastest available version of MARX.
Set up your environment to access all the files and directories which MARX needs:
---(t)csh--- unix% setenv MARX_ROOT <local_marx_directory>/marx-5.5.3 unix% setenv MARX_DATA_DIR ${MARX_ROOT}/share/marx/data unix% setenv PATH ${PATH}:${MARX_ROOT}/bin unix% setenv PFILES ${PFILES}:${MARX_ROOT}/share/marx/pfiles ---bash--- unix% export MARX_ROOT=<local_marx_directory>/marx-5.5.3 unix% export MARX_DATA_DIR=${MARX_ROOT}/share/marx/data unix% export PATH=${PATH}:${MARX_ROOT}/bin unix% export PFILES=${PFILES}:${MARX_ROOT}/share/marx/pfiles
If you installed MARX from the CIAO conda channel then you should set:
---(t)csh--- unix% setenv MARX_ROOT $CONDA_PREFIX ---bash--- unix% export MARX_ROOT=$CONDA_PREFIX
and the rest of the parameters should be set using that value for MARX_ROOT.
Alternatively, the MARX DataDirectory parameter can be defined to point to the data files. By default, this parameter is set to the contents of the $MARX_DATA_DIR environment variable. At this point, your system is ready to run simulations.
Simulating the Source
Before running the simulation, it is necessary to determine the nominal position of the detector during the observation. These values are stored in the header of the level=2 events file:
unix% dmlist acisf04469_repro_evt2.fits header |grep _NOM 0055 RA_NOM 109.6834360799 Real8 Nominal RA 0056 DEC_NOM -24.9551940942 Real8 Nominal Dec 0057 ROLL_NOM 22.3127528406 Real8 Nominal Roll
Additionally, the source coordinates, in decimal degrees, are needed to produce an appropriate PSF, which is (RA, Dec) = (109.6769 deg, -24.954383 deg) as noted earlier.
Other information needed for the simulation is the observation date, which affects the contamination model applied to the detector, and exposure time.
unix% dmkeypar acisf04469_repro_evt2.fits EXPOSURE echo+ 97883.798919246 unix% dmkeypar acisf04469_repro_evt2.fits TSTART echo+ 188535838.52712
The MARX TSTART parameter can be in terms of "mission time" or decimal years. Values <2100 are interpreted as decimal years, otherwise the value is treated as seconds on the spacecraft clock.
Additionally, the appropriate telescope and detector configuration should be set. First, copy over the parameter file locally:
unix% cp $MARX_ROOT/share/marx/pfiles/marx.par ./marx5sim.par
and set the necessary parameters:
unix% pset ./marx5sim ExposureTime=97883.798919246 unix% pset ./marx5sim TStart=188535838.52712 unix% pset ./marx5sim OutputDir=tCanMaj_marxsim.dir unix% pset ./marx5sim SourceRA=109.6769 unix% pset ./marx5sim SourceDEC=-24.954383 unix% pset ./marx5sim RA_Nom=109.6834360799 unix% pset ./marx5sim Dec_Nom=-24.9551940942 unix% pset ./marx5sim Roll_Nom=22.3127528406 unix% pset ./marx5sim DetectorType=ACIS-I unix% pset ./marx5sim GratingType=NONE unix% pset ./marx5sim MirrorType=HRMA
There are a few things to note in the pset commands:
-
Make sure to use the correct detector for the DetectorType parameter; valid options are: HRC-S, ACIS-S, HRC-I, or ACIS-I. Valid options for the GratingType parameter are: HETG, LETG, or NONE. The ACIS array-types are specific, defined sets of CCDs:
- ACIS-I = ACIS-0123
- ACIS-S = ACIS-456789
-
The Exposuretime is set to ensure that the simulated output has the desired exposure length in units of seconds. The "Simulation Control: Exposure Time" section of the MARX manual has more information on setting this parameter.
-
If simulating a source directly on-axis, then SourceRA = RA_NOM and SourceDEC = DEC_NOM. If an off-axis simulation is being performed, they should not be the same.
To define the source being simulated, the ASCII spectrum file created earlier will be spatially distributed as a point source:
unix% pset ./marx5sim SpectrumType=FILE unix% pset ./marx5sim SpectrumFile=tCanMaj.dat unix% pset ./marx5sim SourceType=POINT unix% pset ./marx5sim SourceFlux=-1
The SourceFlux parameter is used to set the overall normalization of the input spectrum. Setting SourceFlux to a positive, non-zero value will cause MARX to re-normalize the spectrum read from the ASCII file to the specified total flux; a negative value will cause MARX to normalize the input spectrum by the specified factor. Using SourceFlux=-1 will use the normalization inherent to the input spectrum.
The telescope dithering can also be included—and is necessary for sub-pixel-scale ACIS analysis.
unix% pset ./marx5sim DitherModel=FILE unix% pset ./marx5sim DitherFile=pcadf04469_000N001_asol1.fits
When simulating a PSF of an observation, the aspect solution from the observation may be used; the standard Chandra Lissajous dither pattern may also be used instead by setting DitherModel=INTERNAL—which will be used when simulating an unobserved source, for example during proposal planning—and the corresponding dither amplitudes to DitherAmp_RA=8 and DitherAmp_Dec=8 for ACIS observations or DitherAmp_RA=20 and DitherAmp_Dec=20 for HRC observations (in arcsec).
Observations are often made with the science instrument module (SIM) is often offset from its nominal position. If these offsets are not included in the MARX run, the simulated PSF will not be placed at the correct location on the detector. The nominal MARX SIM positions are at:
Detector | SIM_X [mm] | SIM_Y [mm] | SIM_Z [mm] |
---|---|---|---|
ACIS-I | -0.78234819833843 | 0 | -233.5924630914 |
ACIS-S | -0.68426746699586 | 0 | -190.1325231040 |
HRC-I | -1.0402925884 | 0 | 126.9854943053 |
HRC-S (spec) | -1.4295857921 | 0 | 250.4559758190 |
HRC-S (image) | -1.5333365632 | 0 | 250.4559758190 |
and can be also looked up in the $MARX_DATA_DIR/caldb/telD1999-07-23aimptsN0002.fits file or by running the MARX ray projection with the default offset values of zero.
If there is a SIM offset from the nominal location, first, compare the SIM values in the original Chandra events file to the ACIS-I values in the table.
unix% dmlist acisf04469_repro_evt2.fits header | grep SIM_ 0039 SIM_X -0.78090834371673 Real8 SIM focus pos (mm) 0040 SIM_Y 0 Real8 SIM orthogonal axis pos (mm) 0041 SIM_Z -233.5874344608 Real8 SIM translation stage pos (mm) MARX SIM_X: -0.78234819833843 MARX SIM_Y: 0 MARX SIM_Z: -233.5924630914
Some observations are done with an offset of several millimeters. The difference, calculated as event_file_value - marx_value, is small in this case:
SIM_X: -0.78090834371673 - (-0.78234819833843) = 0.00143985462170 SIM_Z: -233.5874344608 - (-233.5924630914) = 0.0050286306
The SIM offset generally has a negligible effect, but often manifests itself by placing the source at a different position angle relative to the detector aimpoint. The determined SIM offsets can be then be set:
unix% pset ./marx DetOffsetX=0.001434985462179 unix% pset ./marx DetOffsetY=0 unix% pset ./marx DetOffsetZ=0.0050286306
At the start of the mission, the SIM was located on-axis, but has since drifted due to changes in telescope geometry, with effects that can no longer be neglected. Fortunately, if an aspect solution is used for the simulation's dither model, MARX will account for this drift using the available positional information at all points in time from the aspect solution file.
If MARX's internal dither model is used instead, then the SIM drift can be accounted for, in addition to the SIM offset, in the DetOffset parameters. The drift is characterized in the DY_AVG and DZ_AVG header keywords (in units of millimeters) for an events file that has gone through Repro IV in the archives; has been reprocessed with chandra_repro; or has had r4_header_update applied to it.
unix% dmkeypar acisf00942N004_evt2.fits DY_AVG echo+ 0.0 unix% dmkeypar acisf00942N004_evt2.fits DZ_AVG echo+ 0.0
To obtain the appropriate DetOffset values to run the MARX projection, add the calculated SIM offset values to the average SIM drift values.
DetOffsetX: N/A + 0.00143985462170 = 0.00143985462170 DetOffsetY: 0 + 0 = 0 DetOffsetZ: 0.0 + (0.0050286306) = 0.0050286306
To avoid pixelization effects in the pseudo-events file generated from the simulation, there is an AspectBlur parameter which can be set. Users may experiment with the values of AspectBlur to better match the observation since it may deviate from the default value depending on the source spectral distribution and instrument used. In this particular example, the figures were generated with an aspect blur of ~0.2 arcsec.
unix% pset ./marx5sim AspectBlur=0.19
Should an aspect solution be needed for your analysis, and DitherModel=INTERNAL be used with your MARX simulation, then the marxasp tool can be used.
unix% cp $MARX_ROOT/share/marx/pfiles/marxasp.par . unix% marxasp MarxDir=tCanMaj_marxsim.dir OutputFile=tCanMaj_asol.fits
This asol file can be used in CIAO along with the generated pseudo-events file. Note that if marxasp is used with a simulation where DitherModel≠INTERNAL, an error message is produced.
Now run the tool. Note the syntax (@@) required to use the local parameter file; see Example 9 of ahelp parameter for details.
unix% marx @@./marx5sim.par MARX version 5.5.3, Copyright (C) 2002-2023 Massachusetts Institute of Technology ... screen output omitted... Initializing source type POINT... Reading spectrum from: tCanMaj.dat Your spectrum has a total flux of 5.459085e-04 photons/cm^2/sec System initialized. Starting simulation. Exposure Time set to 9.788380e+04 seconds Collecting 100000 photons... 61571 collected. Reflecting from HRMA Detecting with ACIS-I Writing output to directory 'tCanMaj_marxsim_test' ... Total photons: 61571, Total Photons detected: 8382, (efficiency: 0.136136) (efficiency this iteration 0.136136) Total time: 97884.252890
Using simulate_psf to run MARX
simulate_psf may be used instead of explicitly running MARX and setting all the parameters.
unix% pset simulate_psf infile=acisf04469_repro_evt2.fits unix% pset simulate_psf outroot=tCanMaj_marxsim unix% pset simulate_psf ra=109.6769 unix% pset simulate_psf dec=-24.954383 unix% pset simulate_psf spectrum=tCanMaj.dat unix% pset simulate_psf blur=0.19 unix% pset simulate_psf readout_streak=yes unix% pset simulate_psf pileup=no unix% pset simulate_psf ideal=no unix% pset simulate_psf extended=no unix% simulate_psf
This will replicate the behavior demonstrated in the steps throughout this thread, including the creation of the projected event file and FITS image of the PSF. The key parameters being the source RA and Dec and the reference event file. Many of the MARX parameters that are calculated are automatically determined and set by the script, taking the information from the input event file's header.
The input spectrum for simulate_psf has stricter requirements than the spectrum used directly with MARX. The simulate_psf spectrum must only contain energies between 0.3 and 10 keV; the flux at all the energies must be >0.
There are a couple approaches available to handle these restrictions. The most obvious is when starting from the extracted spectrum of an observation, restrict the noticed energy range to the imposed limits, and set any fluxes ≤0 to a very small positive value. For example:
sherpa> load_data("4469.pi") sherpa> subtract() sherpa> notice("0.3:10.0") sherpa> set_source(polynom1d.truespec) sherpa> truespec.c0 = 1 sherpa> photonflux = get_ratio_plot().y # ph/s/cm**2/keV sherpa> energy = get_ratio_plot().x # keV sherpa> photonflux[photonflux <= 0] = 1e-12 # replace negative and zero fluxes, # from background subtraction, with a # tiny, positive value sherpa> save_arrays("tCanMaj.dat",[energy,photonflux],["keV","ph_s_cm2_keV"],ascii=True)
On the other hand, suppose you already have an existing appropriately formatted ASCII input spectrum, from a model simulation for example, and want to work with it instead. Then omitting all the entries with fluxes ≤0 is a valid approach, and then restricting the energy range between 0.3 and 10 keV with various Numpy tools.
sherpa> import pycrates as pcr sherpa> cr = pcr.read_file("tCanMaj.dat") # read ascii spectrum into a crate sherpa> energy = cr.get_column("KEV").values # load the energy column to a variable sherpa> flux = cr.get_column("PH_S_CM2_KEV").values # load the flux column to a variable # get indicies where the fluxes are > 0 and omit energies <0.3 keV & >10 keV sherpa> idx = (flux > 0) & (energy > 0.3) & (energy <= 10) sherpa> flux2 = flux[idx] sherpa> energy2 = energy[idx] sherpa> save_arrays(tCanMaj_simulate-psf.dat,[energy2,flux2],["keV","ph_s_cm2_keV"],\ ascii=True,clobber=True) # write filtered spectrum to file 'tCanMaj_simulate-psf.dat'
Be aware that the default MARX parameters do not entirely match the default parameters of simulate_psf. In particular, MARX simulates the readout streak and the rays are projected on to a non-ideal detector with QE<1 and pileup affects are not accounted. Furthermore, the chips are not extended to visualize the rays that would otherwise fall onto chip gaps.
simulate_psf in contrast does not simulate the readout streak while extending the visualization into the chip gap and assumes an ideal detector (QE=1) with its default settings.
Create an Events File
MARX creates a number of ASCII files in the specified output directory (tCanMaj_marxsim.dir):
unix% ls tCanMaj_marxsim.dir b_energy.dat det_theta.dat obs.par sky_roll.dat xpos.dat zcos.dat det_dy.dat energy.dat pha.dat time.dat ycos.dat zpos.dat det_dz.dat marx.par sky_dec.dat xcos.dat ypixel.dat detector.dat mirror.dat sky_ra.dat xpixel.dat ypos.dat
These .dat files need to be converted to a FITS events file before they can be used in CIAO. The MARX tool marx2fits does this, given the directory name and the output filename:
unix% marx2fits --pixadj=EDSER tCanMaj_marxsim.dir tCanMaj.fits Reading subpix file Examining tCanMaj_marxsim.dir/time.dat Examining tCanMaj_marxsim.dir/detector.dat Examining tCanMaj_marxsim.dir/energy.dat Examining tCanMaj_marxsim.dir/b_energy.dat Examining tCanMaj_marxsim.dir/xpos.dat Examining tCanMaj_marxsim.dir/ypos.dat Examining tCanMaj_marxsim.dir/zpos.dat Examining tCanMaj_marxsim.dir/xcos.dat Examining tCanMaj_marxsim.dir/ycos.dat Examining tCanMaj_marxsim.dir/zcos.dat Examining tCanMaj_marxsim.dir/xpixel.dat Examining tCanMaj_marxsim.dir/ypixel.dat Examining tCanMaj_marxsim.dir/pha.dat Examining tCanMaj_marxsim.dir/mirror.dat Examining tCanMaj_marxsim.dir/sky_ra.dat Examining tCanMaj_marxsim.dir/sky_dec.dat Examining tCanMaj_marxsim.dir/sky_roll.dat Examining tCanMaj_marxsim.dir/det_dy.dat Examining tCanMaj_marxsim.dir/det_dz.dat Examining tCanMaj_marxsim.dir/det_theta.dat unix%
By default, data obtained from the data archive—and if using the default pix_adj values when reprocessing the data with chandra_repro—has the EDSER sub-pixel event repositioning algorithm applied to ACIS data, and no pixel randomization is applied to HRC data. The --pixadj switch is used to replicate this behavior, where --pixadj=EDSER is used for ACIS and --pixadj=NONE or --pixadj=EXACT for HRC simulations.
The file may be viewed in ds9:
unix% ds9 tCanMaj.fits &
[Version: full-size]
Figure 1: The events file created by MARX
If the objective is to simulate an observation as opposed to generating a model PSF for an observation, then you may want to include pileup effects. First you need to be sure that your simulation parameters exactly match the observation (for example the spectrum flux was not artifically increased to increase sampling of the PSF). If these are not correct, the observed pileup cannot be matched to the simulation.
To include pileup, you must run the marxpileup tool:
unix% cp $MARX_ROOT/share/marx/pfiles/marxpileup.par . unix% marxpileup MarxOutputDir=tCanMaj_marxsim.dir
When creating the events file, to include the pile up effects, use the --pileup flag to process the pileup simulation with marx2fits.
unix% marx2fits --pixadj=EDSER --pileup tCanMaj_marxsim.dir/pileup tCanMaj_pileup.fits
Note: With pileup enabled, it is unclear how to apply an ad-hoc normalization to get the simulation to match the data. One can try to use a region away from the core of the PSF; however, if the observed data does have any extended emission (dust halo, PWN, etc) then the result will be incorrect.
*In MARX 5.0.0, marxpileup introduces an offset on the source position, placing the source between 0.2-0.4 arcsec at 40 degrees from the readout streak, in the direction of the streak. This bug was fixed in MARX 5.1.0.
This pseudo-events file can now be used, for example, to create an image of the PSF.
Sub-pixel Analysis
We can now go ahead and demonstrate an example of using the PSF for imaging analysis.
Since the observed and simulated events files had the EDSER algorithm applied, sub-pixelated images may be created. We will create a 128x128 image, binning by a fifth of the native pixel size. We will use the source's position as the image center, first obtaining its corresponding sky position with dmcoords and then determine the image binning factor.
unix% punlearn dmcoords unix% dmcoords acisf04469_repro_evt2.fits asol=pcadf04469_000N001_asol1.fits \ ? opt=cel celfmt=deg ra=109.6769 dec=-24.954383 unix% pget dmcoords x y 4140.048508882587 4102.357195442711 # x-direction: unix% echo "4140.0-12.8" | bc -l 4127.2 unix% echo "4140.0+12.8" | bc -l 4152.8 # y-direction: unix% echo "4102.4-12.8" | bc -l 4089.6 unix% echo "4102.4+12.8" | bc -l 4115.2
This provides the necessary information to create the sub-pixel images of the observed source and its PSF, 4469_bin0.2.img and tCanMaj_bkgsub_bin0.2.img, respectively.
unix% dmcopy infile="acisf04469_repro_evt2.fits[bin x=4127.2:4152.8:0.2,y=4089.6:4115.2:0.2]" \ ? outfile="4469_bin0.2.img" unix% dmcopy infile="tCanMaj.fits[bin x=4127.2:4152.8:0.2,y=4089.6:4115.2:0.2]" \ ? outfile="tCanMaj_bkgsub_bin0.2.img"
The image of the source can be restored with the arestore tool by deconvolving the PSF from the observed source using the Lucy-Richardson method, which does a good job with bright point sources.
unix% arestore infile=4469_bin0.2.img \ ? psffile=tCanMaj_bkgsub_bin0.2.img \ ? outfile=4469_bkgsub_bin0.2_deconv.img \ ? numiter=256
[Version: full-size]
Figure 2: Deconvolved Images of τ Canis Majoris
To the south of the source in the deconvolved image, there appears to be an unresolved blob, which in all likelihood is not physically real. There is a likely chance that this is an optical artifact from the HRMA that has been identified by the Chandra calibration team and is under investigation. This artifact only affects images on sub-arcsecond scales. The make_psf_asymmetry_region tool can be used to create a region file to overlay over an image of where the artifact will appear on the detector.
unix% make_psf_asymmetry_region infile=acisf04469_repro_evt2.fits \ ? outfile=4469_asym.reg x=4140.0485 y=4102.3572
[Version: full-size]
Figure 3: HRMA Artifact Observed in a Deconvolved Image
The region overlaid on the deconvolved image corresponds to the expected location of the HRMA artifact, indicating that the feature is most likely not physically related to the source.
Encircled Counts Fraction
To get an idea of how well the PSF simulates the source, it may be worthwhile to examine the distribution of counts by looking at the encircled counts fraction (ECF) profile.
unix% ecf_calc infile=acisf04469_repro_evt2.fits outfile=tCanMaj.ecf \ ? radius=8.2 xpos=4140.0485 ypos=4102.3572 binsize=0.2 mode=h unix% ecf_calc tCanMaj.fits outfile=psf.ecf \ ? radius=8.2 xpos=4140.0485 ypos=4102.3572 binsize=0.2 mode=h
The ecf_calc tool is applied on the observed and simulated events files to obtain the ECFs from a circular region, 8.2 sky pixels in radius, centered on the source position in sky coordinates. The profile is binned to match the earlier analysis of 0.2 pixels.
[Version: full-size]
Figure 4: Encircled Counts Fraction Profiles
In this particular realization of the PSF, the MARX generated rays produce a slightly wider core than the observed source within a one pixel radius, but the observed core becomes slightly broader within a three ACIS pixel radius. The wings of the PSF is roughly equivalent to that of the observed.
Summary
This thread demonstrated how to generate ray tracing simulations with MARX and produce pseudo-events files from the results.
History
31 Jul 2014 | original version |
12 Feb 2016 | updated to use MARX 5.2.0. |
06 Apr 2016 | revised AspectBlur values. |
11 Apr 2016 | Added warning about installing MARX on OSX with default C compiler. |
12 Apr 2016 | added information on using simulate_psf. |
10 Jun 2016 | Revised information about handling the SIM offset and added information about the MARX AspectBlur parameter. |
20 Jun 2016 | Fixed typos for suggested values in link to AspectBlur why page. |
10 May 2017 | Updated running marx2fits with --pileup. |
17 Aug 2017 | fixed typos. |
27 Oct 2017 | added admonition about simulate_psf input spectrum restrictions. |
30 Mar 2018 | Removed warning about clang compiler on OSX. |
01 Aug 2019 | added bash setup instructions. |
26 Jan 2021 | added conda setup instructions. |
31 Jan 2022 | Review for CIAO 4.14. Updated for Repro5 and CALDB 4.9.6. |
21 Mar 2023 | Replaced references to ${MARX_DIR} to ${MARX_ROOT}. |
27 Apr 2023 | revised AspectBlur description. |
23 Oct 2024 | revised and simplified Python/NumPy filtering syntax in input spectrum restrictions admonition. |