TypeIaSED#
- class uvex_transients.models.supernovae.Ia.TypeIaSED(**overrides: Parameter | Quantity | float | int)[source]#
Type Ia supernova SED, with priors fit to a ZTF sample of SNe Ia.
Reuses
ArnettDecaySED’s radioactive-decay Arnett diffusion and floored-photosphere blackbody entirely; only_DEFAULT_PARAMETERSdiffers. The priors follow Sarin et al.[1] (Sarin et al. 2026, a sample of 2205 SNe Ia from ZTF):M_NiandM_ejare the population-level Gaussians from that paper’s hierarchical Arnett-model fit (\(\mu_\mathrm{Ni}=0.64\,M_\odot\), \(\sigma_\mathrm{Ni}=0.42\,M_\odot\); \(\mu_\mathrm{ej}=1.26\,M_\odot\), \(\sigma_\mathrm{ej}=0.33\,M_\odot\)),kappa_gammais fixed at the value adopted by Scalzo et al.[2] (Scalzo et al. 2014), andkappais uniform over that paper’s marginalization range.Parameters
Parameter
Symbol
Description
M_Ni\(M_\mathrm{Ni}\)
Nickel-56 mass synthesized in the explosion.
M_ej\(M_\mathrm{ej}\)
Ejecta mass.
v_ej\(v_\mathrm{ej}\)
Ejecta velocity, taken to be constant and equal to the photospheric velocity.
kappa\(\kappa\)
Grey optical opacity.
kappa_gamma\(\kappa_\gamma\)
Opacity to high-energy photons. Fixed.
T_floor\(T_\mathrm{floor}\)
Minimum photospheric temperature.
References
Methods
as_astropy_model([x_type, y_type, y_kind, ...])Build an
Modelof thisSpectralModelfor a given parameter set.as_source_spectrum(t, *[, redshift, ...])Build a
SourceSpectrumgiving the observed flux at one fixed time \(t\).eval(nu, t, **parameters)Evaluate the spectral luminosity at the given frequency and time.
eval_bolometric(t, **parameters)Evaluate the bolometric luminosity at the given time.
eval_bolometric_cgs(t, **parameters)Bolometric luminosity, taking and returning plain cgs numbers.
eval_bolometric_log(t, **parameters)Natural log of the bolometric luminosity, given physical-unit inputs.
eval_bolometric_log_cgs(t, **parameters)Natural log of the bolometric luminosity, taking and returning plain cgs numbers.
eval_cgs(nu, t, **parameters)Spectral luminosity, taking and returning plain cgs numbers.
eval_from_arrays(nu, t, *parameters)Positional-argument form of
eval().eval_log(nu, t, **parameters)Natural log of the spectral luminosity, given physical-unit inputs.
eval_log_cgs(nu, t, **parameters)Natural log of the spectral luminosity, taking and returning plain cgs numbers.
eval_spectrum(nu, t, **parameters)Evaluate the normalized spectral shape at the given frequency and time.
eval_spectrum_cgs(nu, t, **parameters)Return the normalized spectral shape as plain cgs numbers; see
eval_log_cgs().eval_spectrum_log(nu, t, **parameters)Natural log of the normalized spectral shape, given physical-unit inputs.
eval_spectrum_log_cgs(nu, t, **parameters)Natural log of the normalized spectral shape, taking and returning plain cgs numbers.
flux(nu, t, *[, redshift, ...])Evaluate the observed flux density at the given frequency and time.
flux_band(nu, throughput, t, *[, redshift, ...])Evaluate the throughput-weighted mean observed flux density over a band.
flux_band_cgs(nu, throughput, t, redshift, ...)Band-averaged observed flux density as plain cgs numbers; see
flux_band_log_cgs().flux_band_log(nu, throughput, t, *[, ...])Natural log of the band-averaged observed flux density, given physical-unit inputs.
flux_band_log_cgs(nu, throughput, t, ...[, ...])Natural log of the throughput-weighted mean flux density over a band, plain cgs numbers.
flux_bolometric(t, *[, redshift, ...])Evaluate the observed bolometric flux at the given time.
flux_bolometric_cgs(t, redshift, ...)Observed bolometric flux, taking and returning plain cgs numbers.
flux_bolometric_log(t, *[, redshift, ...])Natural log of the observed bolometric flux, given physical-unit inputs.
flux_bolometric_log_cgs(t, redshift, ...)Natural log of the observed bolometric flux, taking and returning plain cgs numbers.
flux_cgs(nu, t, redshift, luminosity_distance, *)Observed flux density, taking and returning plain cgs numbers.
flux_log(nu, t, *[, redshift, ...])Natural log of the observed flux density, given physical-unit inputs.
flux_log_cgs(nu, t, redshift, ...[, ...])Natural log of the observed flux density, taking and returning plain cgs numbers.
get(k[,d])items()keys()mag(nu, t, *[, redshift, ...])Evaluate the apparent AB magnitude at the given frequency and time.
mag_band(nu, throughput, t, *[, redshift, ...])Evaluate the apparent AB magnitude of the band-averaged flux density.
mag_band_cgs(nu, throughput, t, redshift, ...)Apparent AB magnitude of the band-averaged flux density.
mag_bandpass(bandpass, t, *[, redshift, ...])Evaluate the apparent AB magnitude of the flux averaged over bandpass.
mag_cgs(nu, t, redshift, luminosity_distance, *)Apparent AB magnitude: \(m_\mathrm{AB} = -2.5 \log_{10}(F_\nu / F_{\mathrm{AB},0})\).
pack_params_to_arrays(**parameters)Convert a dict of parameter values into an ordered sequence.
sample_parameters([size, rng, parameters])Draw random samples of some or all of this model's parameters.
simulate(nu, t[, size, rng])Draw random parameter realizations and evaluate the model at the given frequency and time.
simulate_photometry(t, exptime, detector, ...)Simulate noisy synthetic photometry of this model at given time(s), against a real detector.
temperature(t, **parameters)\(T(t)\) in Kelvin.
unpack_params_from_arrays(*parameters)Convert an ordered sequence of parameter values back into a dict.
values()