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)

{'intrinsic': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fdca00>, 'old_intrinsic': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fddba0>, 'old_reprocessed': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fddc90>, 'old_nebular': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fddc00>, 'old_nebular_continuum': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fdc760>, 'old_linecont': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fddab0>, 'old_transmitted': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fdd8d0>, 'old_escaped': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fddae0>, 'young_intrinsic': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fdd570>, 'young_reprocessed': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fdd420>, 'young_nebular': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fdd8a0>, 'young_nebular_continuum': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fdd750>, 'young_linecont': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fdff40>, 'young_transmitted': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fdd3f0>, 'young_escaped': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fdd540>, 'attenuated': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fdc940>, 'old_attenuated': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fddf30>, 'young_attenuated': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fe4eb0>, 'young_attenuated_nebular': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fe4c70>}
{'intrinsic': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fe7a90>, 'old_intrinsic': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fdfbb0>, 'old_reprocessed': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fe50c0>, 'old_nebular': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fdc970>, 'old_nebular_continuum': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fe6c50>, 'old_linecont': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fdcaf0>, 'old_transmitted': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fe6d40>, 'old_escaped': <synthesizer.photometry.PhotometryCollection object at 0x7fa4fbffb940>, 'young_intrinsic': <synthesizer.photometry.PhotometryCollection object at 0x7fa4fbffbb20>, 'young_reprocessed': <synthesizer.photometry.PhotometryCollection object at 0x7fa4fbffbca0>, 'young_nebular': <synthesizer.photometry.PhotometryCollection object at 0x7fa4fbffbeb0>, 'young_nebular_continuum': <synthesizer.photometry.PhotometryCollection object at 0x7fa4fbffbe80>, 'young_linecont': <synthesizer.photometry.PhotometryCollection object at 0x7fa4fbff8e80>, 'young_transmitted': <synthesizer.photometry.PhotometryCollection object at 0x7fa4fbffa8f0>, 'young_escaped': <synthesizer.photometry.PhotometryCollection object at 0x7fa4a3324dc0>, 'attenuated': <synthesizer.photometry.PhotometryCollection object at 0x7fa4a3324f70>, 'old_attenuated': <synthesizer.photometry.PhotometryCollection object at 0x7fa4a3325120>, 'young_attenuated': <synthesizer.photometry.PhotometryCollection object at 0x7fa4a33252d0>, 'young_attenuated_nebular': <synthesizer.photometry.PhotometryCollection object at 0x7fa4a3325480>}

Or on the galaxy level

print(gal.photo_lnu)

{'total': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fe7a60>, 'dust_emission': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fe6ce0>, 'total_intrinsic': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fe6c80>, 'total_attenuated': <synthesizer.photometry.PhotometryCollection object at 0x7fa544fe64d0>}

As before we can print the photometry.

print(gal.photo_fnu["total_attenuated"])

------------------------------------------------------------------
|                       PHOTOMETRY (FLUX)                        |
|------------------------------------|---------------------------|
| JWST/NIRCam.F090W (λ = 9.02e+03 Å) | 1.20e-27 erg/(Hz*cm**2*s) |
|------------------------------------|---------------------------|
| JWST/NIRCam.F150W (λ = 1.50e+04 Å) | 2.34e-28 erg/(Hz*cm**2*s) |
|------------------------------------|---------------------------|
| JWST/NIRCam.F200W (λ = 1.99e+04 Å) | 5.02e-28 erg/(Hz*cm**2*s) |
|------------------------------------|---------------------------|
| JWST/NIRCam.F277W (λ = 2.76e+04 Å) | 3.35e-28 erg/(Hz*cm**2*s) |
|------------------------------------|---------------------------|
| JWST/NIRCam.F356W (λ = 3.57e+04 Å) | 1.05e-27 erg/(Hz*cm**2*s) |
|------------------------------------|---------------------------|
| JWST/NIRCam.F444W (λ = 4.40e+04 Å) | 1.78e-27 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)

0.014417603732710274 Mpc 0.014432401643262961 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)

0.009309412277303435 Mpc 0.020503374559556278 Mpc 0.009307128310853577 Mpc 0.020515571331240084 Mpc