Generating photometry from a Galaxy

If you are working with a Galaxy (or many Galaxy objects) containing multiple spectra, you can use the galaxy level get_photo_lnu and get_photo_fluxes methods to generate photometry for all spectra in the galaxy.

Before we can demonstrate this we firs need to make a parametric galaxy with a Stars and Blackhole component, define an emission model for a whole galaxy and generate their rest–frame and observed spectra.

import numpy as np
from astropy.cosmology import Planck18 as cosmo
from unyt import Mpc, Msun, Myr, kelvin, yr

from synthesizer.emission_models import (
    AttenuatedEmission,
    BimodalPacmanEmission,
    DustEmission,
    EmissionModel,
    UnifiedAGN,
)
from synthesizer.emission_models.attenuation import PowerLaw
from synthesizer.emission_models.dust.emission import Blackbody, Greybody
from synthesizer.filters import FilterCollection
from synthesizer.grid import Grid
from synthesizer.parametric import SFH, ZDist
from synthesizer.parametric import Stars as ParametricStars
from synthesizer.particle import BlackHoles, Galaxy
from synthesizer.particle.stars import sample_sfzh

# Get the grids which we'll need for extraction
grid_dir = "../../../tests/test_grid"
grid_name = "test_grid"
grid = Grid(grid_name, grid_dir=grid_dir)
nlr_grid = Grid("test_grid_agn-nlr", grid_dir="../../../tests/test_grid")
blr_grid = Grid("test_grid_agn-blr", grid_dir="../../../tests/test_grid")

# Define the metallicity history
zh = ZDist.DeltaConstant(metallicity=0.01)

# Define the star formation history
sfh_p = {"max_age": 100 * Myr}
sfh = SFH.Constant(**sfh_p)

# Initialise the parametric Stars object
param_stars = ParametricStars(
    grid.log10age,
    grid.metallicity,
    sf_hist=sfh,
    metal_dist=zh,
    initial_mass=10**9 * Msun,
)

# Define the number of stellar particles we want
n = 500

# Sample the parametric SFZH, producing a particle Stars object
# we will also pass some keyword arguments for some example attributes
part_stars = sample_sfzh(
    sfzh=param_stars.sfzh,
    log10ages=param_stars.log10ages,
    log10metallicities=param_stars.log10metallicities,
    nstar=n,
    current_masses=np.full(n, 10**8.7 / n) * Msun,
    redshift=1,
    coordinates=np.random.normal(0, 0.01, (n, 3)) * Mpc,
    centre=np.zeros(3) * Mpc,
)

# Make fake properties
n = 4
masses = 10 ** np.random.uniform(low=7, high=9, size=n) * Msun
coordinates = np.random.normal(0, 0.01, (n, 3)) * Mpc
accretion_rates = 10 ** np.random.uniform(low=-2, high=1, size=n) * Msun / yr
metallicities = np.full(n, 0.01)

# And get the black holes object
blackholes = BlackHoles(
    masses=masses,
    coordinates=coordinates,
    accretion_rates=accretion_rates,
    metallicities=metallicities,
)

# And create the galaxy
gal = Galaxy(
    stars=part_stars,
    black_holes=blackholes,
    redshift=1,
)

# Get the stellar pacman model
pc_model = BimodalPacmanEmission(
    grid=grid,
    tau_v_ism=1.0,
    tau_v_birth=0.7,
    dust_curve_ism=PowerLaw(slope=-1.3),
    dust_curve_birth=PowerLaw(slope=-0.7),
    dust_emission_ism=Blackbody(temperature=100 * kelvin),
    dust_emission_birth=Blackbody(temperature=30 * kelvin),
    fesc=0.2,
    fesc_ly_alpha=0.9,
    label="stellar_total",
)

# Get the UnifiedAGN model
uni_model = UnifiedAGN(
    nlr_grid,
    blr_grid,
    covering_fraction_nlr=0.1,
    covering_fraction_blr=0.1,
    torus_emission_model=Blackbody(1000 * kelvin),
    label="agn_intrinsic",
)

# Define an emission model to attenuate the intrinsic AGN emission
att_uni_model = AttenuatedEmission(
    dust_curve=PowerLaw(slope=-1.0),
    apply_dust_to=uni_model,
    tau_v=0.7,
    emitter="blackhole",
    label="agn_attenuated",
)

gal_intrinsic = EmissionModel(
    label="total_intrinsic",
    combine=(uni_model, pc_model["intrinsic"]),
    emitter="galaxy",
)

gal_attenuated = EmissionModel(
    label="total_attenuated",
    combine=(att_uni_model, pc_model["attenuated"]),
    related_models=(gal_intrinsic,),
    emitter="galaxy",
)

# And now include the dust emission
gal_dust = DustEmission(
    dust_emission_model=Greybody(30 * kelvin, 1.2),
    dust_lum_intrinsic=gal_intrinsic,
    dust_lum_attenuated=gal_attenuated,
    emitter="galaxy",
    label="dust_emission",
)

gal_total = EmissionModel(
    label="total",
    combine=(gal_attenuated, gal_dust),
    related_models=(gal_intrinsic),
    emitter="galaxy",
)

# Get the spectra
sed = gal.get_spectra(gal_total)

# Get fluxes
gal.get_observed_spectra(cosmo)

We can then combine with a FilterCollection to generate the galaxy-level photometry.

# Get the filter collection
fs = [
    f"JWST/NIRCam.{f}"
    for f in ["F090W", "F150W", "F200W", "F277W", "F356W", "F444W"]
]

filters = FilterCollection(
    filter_codes=fs,
    new_lam=grid.lam,
)

# Get the photometry
gal.get_photo_lnu(filters)
gal.get_photo_fnu(filters)

The photometry produced by these methods are stored in the photo_lnu and photo_fluxes attributes, either at the base galaxy level or the individual components. These attributes are dictionaries containing the photometry for each spectra key.

For example, on the Galaxy.Stars object:

print(gal.stars.photo_lnu)
print(gal.stars.photo_fnu)

{'attenuated': <synthesizer.photometry.PhotometryCollection object at 0x7fd525026fe0>, 'old_attenuated': <synthesizer.photometry.PhotometryCollection object at 0x7fd525025c00>, 'old_reprocessed': <synthesizer.photometry.PhotometryCollection object at 0x7fd525026e30>, 'old_nebular': <synthesizer.photometry.PhotometryCollection object at 0x7fd5250268c0>, 'old_nebular_continuum': <synthesizer.photometry.PhotometryCollection object at 0x7fd525025ba0>, 'old_linecont': <synthesizer.photometry.PhotometryCollection object at 0x7fd525027130>, 'old_transmitted': <synthesizer.photometry.PhotometryCollection object at 0x7fd5250264d0>, 'young_attenuated': <synthesizer.photometry.PhotometryCollection object at 0x7fd525025db0>, 'young_attenuated_nebular': <synthesizer.photometry.PhotometryCollection object at 0x7fd525026530>, 'young_reprocessed': <synthesizer.photometry.PhotometryCollection object at 0x7fd525026e60>, 'young_nebular': <synthesizer.photometry.PhotometryCollection object at 0x7fd5250261a0>, 'young_nebular_continuum': <synthesizer.photometry.PhotometryCollection object at 0x7fd525033850>, 'young_linecont': <synthesizer.photometry.PhotometryCollection object at 0x7fd525033640>, 'young_transmitted': <synthesizer.photometry.PhotometryCollection object at 0x7fd525033130>, 'intrinsic': <synthesizer.photometry.PhotometryCollection object at 0x7fd525033040>, 'young_intrinsic': <synthesizer.photometry.PhotometryCollection object at 0x7fd525032ef0>, 'young_escaped': <synthesizer.photometry.PhotometryCollection object at 0x7fd525032b90>, 'old_intrinsic': <synthesizer.photometry.PhotometryCollection object at 0x7fd525032a40>, 'old_escaped': <synthesizer.photometry.PhotometryCollection object at 0x7fd525032980>}
{'attenuated': <synthesizer.photometry.PhotometryCollection object at 0x7fd525031f00>, 'old_attenuated': <synthesizer.photometry.PhotometryCollection object at 0x7fd525026020>, 'old_reprocessed': <synthesizer.photometry.PhotometryCollection object at 0x7fd525030670>, 'old_nebular': <synthesizer.photometry.PhotometryCollection object at 0x7fd525026d10>, 'old_nebular_continuum': <synthesizer.photometry.PhotometryCollection object at 0x7fd525032380>, 'old_linecont': <synthesizer.photometry.PhotometryCollection object at 0x7fd4d700f490>, 'old_transmitted': <synthesizer.photometry.PhotometryCollection object at 0x7fd525027040>, 'young_attenuated': <synthesizer.photometry.PhotometryCollection object at 0x7fd525030370>, 'young_attenuated_nebular': <synthesizer.photometry.PhotometryCollection object at 0x7fd4cdf75210>, 'young_reprocessed': <synthesizer.photometry.PhotometryCollection object at 0x7fd4cdf753c0>, 'young_nebular': <synthesizer.photometry.PhotometryCollection object at 0x7fd4cdf75570>, 'young_nebular_continuum': <synthesizer.photometry.PhotometryCollection object at 0x7fd4cdf75720>, 'young_linecont': <synthesizer.photometry.PhotometryCollection object at 0x7fd4cdf758d0>, 'young_transmitted': <synthesizer.photometry.PhotometryCollection object at 0x7fd4cdf75a80>, 'intrinsic': <synthesizer.photometry.PhotometryCollection object at 0x7fd4cdf75c30>, 'young_intrinsic': <synthesizer.photometry.PhotometryCollection object at 0x7fd4cdf75de0>, 'young_escaped': <synthesizer.photometry.PhotometryCollection object at 0x7fd4cdf75f90>, 'old_intrinsic': <synthesizer.photometry.PhotometryCollection object at 0x7fd4cdf76140>, 'old_escaped': <synthesizer.photometry.PhotometryCollection object at 0x7fd4cdf762f0>}

Or on the galaxy level

print(gal.photo_lnu)

{'total': <synthesizer.photometry.PhotometryCollection object at 0x7fd525030d30>, 'total_attenuated': <synthesizer.photometry.PhotometryCollection object at 0x7fd525031e40>, 'dust_emission': <synthesizer.photometry.PhotometryCollection object at 0x7fd525031ff0>, 'total_intrinsic': <synthesizer.photometry.PhotometryCollection object at 0x7fd5250321a0>}

As before we can print the photometry.

print(gal.photo_fnu["total_attenuated"])

------------------------------------------------------------------
|                       PHOTOMETRY (FLUX)                        |
|------------------------------------|---------------------------|
| JWST/NIRCam.F090W (λ = 9.02e+03 Å) | 5.35e-29 erg/(Hz*cm**2*s) |
|------------------------------------|---------------------------|
| JWST/NIRCam.F150W (λ = 1.50e+04 Å) | 2.46e-29 erg/(Hz*cm**2*s) |
|------------------------------------|---------------------------|
| JWST/NIRCam.F200W (λ = 1.99e+04 Å) | 3.28e-29 erg/(Hz*cm**2*s) |
|------------------------------------|---------------------------|
| JWST/NIRCam.F277W (λ = 2.76e+04 Å) | 6.26e-29 erg/(Hz*cm**2*s) |
|------------------------------------|---------------------------|
| JWST/NIRCam.F356W (λ = 3.57e+04 Å) | 2.40e-28 erg/(Hz*cm**2*s) |
|------------------------------------|---------------------------|
| JWST/NIRCam.F444W (λ = 4.40e+04 Å) | 5.55e-28 erg/(Hz*cm**2*s) |
------------------------------------------------------------------

Or plot them.

gal.photo_fnu["total_attenuated"].plot_photometry(show=True)

(<Figure size 350x500 with 2 Axes>,
 <Axes: xlabel='$\\lambda_\\mathrm{obs}/[\\mathrm{\\AA}]$', ylabel='$F/[\\mathrm{\\rm{erg} \\ / \\ \\rm{Hz \\cdot \\rm{cm}^{2} \\cdot \\rm{s}}}]$'>)

gal.photo_fnu["total_intrinsic"].plot_photometry(show=True)

(<Figure size 350x500 with 2 Axes>,
 <Axes: xlabel='$\\lambda_\\mathrm{obs}/[\\mathrm{\\AA}]$', ylabel='$F/[\\mathrm{\\rm{erg} \\ / \\ \\rm{Hz \\cdot \\rm{cm}^{2} \\cdot \\rm{s}}}]$'>)

gal.photo_fnu["total"].plot_photometry(show=True)

(<Figure size 350x500 with 2 Axes>,
 <Axes: xlabel='$\\lambda_\\mathrm{obs}/[\\mathrm{\\AA}]$', ylabel='$F/[\\mathrm{\\rm{erg} \\ / \\ \\rm{Hz \\cdot \\rm{cm}^{2} \\cdot \\rm{s}}}]$'>)

Calculating light radii

Once we have photometry we can calculate the radius enclosing a given fraction of the light for a component. Here we’ll calculate the half light radius for both the intrinsic emission and the total emission in “F444W” in terms of luminosity, but before we can do that we need to get the particle spectra and call get_particle_photo_lnu to first calculate the per particle photometry (above we used the galaxy level methods to calculate integrated spectra).

# Get the particle spectra
pc_model.set_per_particle(True)
gal.stars.get_spectra(pc_model)

# Get the particle photometry
gal.stars.get_particle_photo_lnu(filters)

int_r50 = gal.stars.get_half_luminosity_radius(
    "intrinsic", "JWST/NIRCam.F444W"
)
tot_r50 = gal.stars.get_half_luminosity_radius(
    "stellar_total", "JWST/NIRCam.F444W"
)
print(int_r50, tot_r50)

0.016939812412057564 Mpc 0.01690144346103718 Mpc

Similarly to the “attr” radii we can compute for any particle component, we can also compute the radius enclosing any fraction of the light for any particle component.

int_r20 = gal.stars.get_luminosity_radius(
    "intrinsic", "JWST/NIRCam.F444W", frac=0.2
)
tot_r20 = gal.stars.get_luminosity_radius(
    "stellar_total", "JWST/NIRCam.F444W", frac=0.2
)
int_r80 = gal.stars.get_luminosity_radius(
    "intrinsic", "JWST/NIRCam.F444W", frac=0.8
)
tot_r80 = gal.stars.get_luminosity_radius(
    "stellar_total", "JWST/NIRCam.F444W", frac=0.8
)
print(int_r20, int_r80, tot_r20, tot_r80)

0.011472944549617193 Mpc 0.02410510963418599 Mpc 0.01145091170873261 Mpc 0.024027921114464425 Mpc