Photometry

CAESAR can optionally compute photometry for any object(s) in any available FSPS band. This is done as in Pyloser: Compute the dust extinction to each star based on the line-of-sight dust column, attenuate its spectrum with a user-selectable attenuation law, sum the spectra of all stars in the object, and apply the desired bandpasses.

NOTE: CAESAR accounts for dust but does not do proper dust radiative transfer! To e.g. model the far-IR spectrum or predict extinction laws, you can use Powderday. The main advantage of CAESAR is speed. Also, it gives the user more direct control over the attenuation law used, which may be desirable in some instances. Results are similar to Powderday for most galaxies, but differences at the level of ~0.1 magnitudes are not uncommon.

Installation

To compute photometry, two additional packages must be installed:

  • python-fsps: Follow the instructions, which requires installing and compiling FSPS.

  • synphot: Available via pip or in conda-forge.

Running stand-alone

The photometry module can also be run stand-alone for specified objects. Any object with stars and gas (stored in slist and glist) can have its photometry computed. To do so, first create a photometry object, and then apply run_pyloser() to it.

For example, to run photometry for all halos in a pre-existing CAESAR catalog:

In [1]: from caesar.pyloser.pyloser import photometry
In [2]: ds  = yt.load(SNAP)
In [3]: sim = caesar.load('my_caesar_file.hdf5')
In [4]: galphot = photometry(sim,sim.halos,ds=ds,band_names='sdss',nproc=16)
In [5]: galphot.run_pyloser()

All options as listed under “Photometry Options” are passable to photometry. The computed SDSS photometry will be available in the usual dictionaries absmag, absmag_nodust, appmag, and appmag_nodust, for each halo.

Photometry Options

The following options can be passed to member_search() or when instantiating the photometry class:

  • band_names: (REQUIRED): The list of band(s) to compute, selected from python-fsps (use fsps.list_filters() to see options). You can also specify a substring (min. 4 characters) to do all bands that contain that substring, e.g. 'sdss' will compute all available SDSS bands. The v band is always computed; the difference between the absmag and absmag_nodust gives A_V. There are two special options: 'all' computes all FSPS bands, while 'uvoir' computes all bands bluewards of 5 microns. Default: ['v']

  • ssp_table_file: Filename containing FSPS spectra lookup table. If it doesn’t exist, it is generated assuming a Chabrier IMF with nebular emission and saved to this filename for future use. If you prefer different FSPS options, first generate it using generate_SSP_table, and read it in here. Default: 'SSP_Chab_EL.hdf5'

  • ext_law: Specifies the extinction law to use. Current options are calzetti, chevallard, conroy, cardelli (equivalently mw), smc, and lmc. There are two composite extinction laws available: mix_calz_mw uses mw for galaxies with specific star formation rate sSFR<0.1 Gyr^-1, calzetti for sSFR>1, and a linear combination in between. composite additionally adds a metallicity dependence, using mix_calz_mw for Z>Solar, smc for Z<0.1*Solar, and a linear combination in between. Default: 'composite'

  • view_dir: Sets viewing direction for computing LOS extinction. Choices are x, y, z. Default: 'x'

  • use_dust: If present, uses the particles’ dust masses to compute the LOS extinction. Otherwise uses the metals, with an assumed dust-to-metals ratio of 0.4, reduced for sub-solar metallicities. Default: True

  • use_cosmic_ext: Applies redshift-dependent Madau(1995) IGM attenuation to spectra. This is computed using synphot.etau_madau(). Default: True

  • nproc: Number of cores to use. If -1, it tries to use the CAESAR object’s value, or else defaults to 1. Default: -1

Generating a lookup table

If you don’t want Caesar’s default choices of Chabrier IMF and nebular emission with all other options set to the python-FSPS default, you will need to create a new table and specify it with ssp_table_file when instantiating photometry.

To create a new SSP lookup table, run generate_ssp_table with the desired FSPS options. For example:

In [1]: from caesar.pyloser.pyloser import generate_ssp_table
In [2]: generate_ssp_table('my_new_SSP_table.hdf5',Zsol=0.0134,oversample=[2,2],imf_type=1,add_neb_emission=True,sfh=0,zcontinuous=1)

Options:

  • oversample oversamples in [age,metallicity] by the specified factors from the native FSPS ranges, in order to get more accurate interpolation. Note that setting these >1 creates a larger output file, by the product of those values. Default: [2,2]

  • Zsol sets the metallicity in solar units in order to convert the FSPS metallicity values into a solar abundance scale. Default: Solar['total'] (see pyloser.py)

  • The remaining **kwargs options are passed directly to fsps.StellarPopulations, so any stellar population available in python-FSPS can be generated. NOTE: sfh=0 and zcontinuous=1 should always be used.

If you have a lookup table and don’t know the options used to generate it, you can list the fsps_options data block using the h5dump command at the system prompt:

% h5dump -d fsps_options my_new_SSP_table.hdf5

This will give you a bunch of hdf5 header info but at the end will be the DATA block which lists the FSPS options used.

Performance tips

  • The code is cython parallelized over objects, so for efficiency it is best to run many objects within a single photometry instance. Try not to do a single galaxy at a time!

  • Generally, computing the extinction and spectra takes most of the time; once the spectra are computed, applying bandpasses is fast. So it is also better to generate as many bands as possible in one call.