Cosmological Source Catalog

SOXS provides the make_cosmological_sources_file() function to generate a set of photons from cosmological halos and store them in a SIMPUT catalog.

First, import our modules:

import matplotlib

matplotlib.rc("font", size=18)
import soxs

Second, define our parameters, including the location within the catalog where we are pointed via the argument cat_center. To aid in picking a location, see the halo map.

exp_time = (200.0, "ks")
fov = 20.0  # in arcmin
sky_center = [30.0, 45.0]  # in degrees
cat_center = [3.1, -1.9]

Now, use make_cosmological_sources_file() to create a SIMPUT catalog made up of photons from the halos. We’ll set a random seed using the prng parameter to make sure we get the same result every time. We will also write the halo properties to an ASCII table for later analysis, using the output_sources parameter:

soxs.make_cosmological_sources_file(
    "my_cat.simput",
    "cosmo",
    exp_time,
    fov,
    sky_center,
    cat_center=cat_center,
    prng=33,
    overwrite=True,
)

soxs : [INFO     ] 2025-02-18 13:58:07,305 Creating photons from cosmological sources.
soxs : [INFO     ] 2025-02-18 13:58:07,305 Loading halo data from catalog: /Users/jzuhone/Source/soxs/soxs/files/halo_catalog.h5
soxs : [INFO     ] 2025-02-18 13:58:07,381 Coordinates of the FOV within the catalog are (3.1, -1.9) deg.
soxs : [INFO     ] 2025-02-18 13:58:07,381 Selecting halos in the FOV.
soxs : [INFO     ] 2025-02-18 13:58:07,385 Number of halos in the field of view: 384

soxs : [INFO     ] 2025-02-18 13:58:17,768 Created 5786907 photons from cosmological sources.
soxs : [INFO     ] 2025-02-18 13:58:17,855 Appending source 'cosmo' to my_cat.simput.

<soxs.simput.SimputCatalog at 0x13fe2b4d0>

Next, use the instrument_simulator() to simulate the observation:

soxs.instrument_simulator(
    "my_cat.simput",
    "cosmo_cat_evt.fits",
    exp_time,
    "lynx_hdxi",
    sky_center,
    overwrite=True,
)

soxs : [INFO     ] 2025-02-18 13:58:18,032 Simulating events from 1 sources using instrument lynx_hdxi for 200 ks.
soxs : [INFO     ] 2025-02-18 13:58:19,040 Scattering energies with RMF xrs_hdxi.rmf.

soxs : [INFO     ] 2025-02-18 13:58:21,569 Detected 2164576 events in total.
soxs : [INFO     ] 2025-02-18 13:58:21,701 Adding background events.
soxs : [INFO     ] 2025-02-18 13:58:21,857 Adding in point-source background.
soxs : [INFO     ] 2025-02-18 13:58:37,376 Simulating events from 1 sources using instrument lynx_hdxi for 200 ks.
soxs : [INFO     ] 2025-02-18 13:58:43,006 Scattering energies with RMF xrs_hdxi.rmf.

soxs : [INFO     ] 2025-02-18 13:58:47,514 Detected 3868869 events in total.
soxs : [INFO     ] 2025-02-18 13:58:47,551 Generated 3868869 photons from the point-source background.
soxs : [INFO     ] 2025-02-18 13:58:47,551 Adding in astrophysical foreground.

soxs : [INFO     ] 2025-02-18 13:58:57,763 Adding in instrumental background.
soxs : [INFO     ] 2025-02-18 13:58:59,254 Making 33736334 events from the galactic foreground.
soxs : [INFO     ] 2025-02-18 13:58:59,256 Making 523354 events from the instrumental background.
soxs : [INFO     ] 2025-02-18 13:59:06,463 Observation complete.
soxs : [INFO     ] 2025-02-18 13:59:06,466 Writing events to file cosmo_cat_evt.fits.

We can use the write_image() function in SOXS to bin the events into an image and write them to a file, restricting the energies between 0.7 and 7.0 keV:

soxs.write_image(
    "cosmo_cat_evt.fits", "cosmo_img.fits", emin=0.7, emax=7.0, overwrite=True
)

We can now show the resulting image:

fig, ax = soxs.plot_image(
    "cosmo_img.fits",
    stretch="sqrt",
    cmap="cubehelix",
    vmin=0.0,
    vmax=2.0,
    width=0.33333,
)