TypeIcBLSED#

class uvex_transients.models.supernovae.IcBL.TypeIcBLSED(**overrides: Parameter | Quantity | float | int)[source]#

Type Ic-BL (broad-lined) supernova SED, with priors fit to a ZTF sample of SNe Ic-BL.

Reuses ArnettDecaySED’s radioactive-decay Arnett diffusion and floored-photosphere blackbody entirely, exactly as TypeIaSED does; only _DEFAULT_PARAMETERS differs. The priors on M_Ni, M_ej and v_ej are sample statistics (mean, sample standard deviation) of the 36-event explosion-property table of Srinivasaragavan et al.[1] (nickel mass, kinetic energy, ejecta mass and photospheric velocity per event). One event (SN 2020wgz), whose reported \(M_\mathrm{Ni}=2.46\,M_\odot\) is a >5-sigma outlier driven by an e_k/m_ej lower limit rather than a measurement, is excluded from the M_Ni statistics. M_ej uses only rows with a measured (non-lower-limit) value, and v_ej is identified with the sample’s photospheric velocities (v_ph), regardless of the epoch quoted. kappa and T_floor are not constrained by that table and are left at TypeIaSED’s values; kappa_gamma is instead fixed at a large value (full gamma-ray trapping across the simulated window), unlike TypeIaSED’s Scalzo+14 value.

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 Model of this SpectralModel for a given parameter set.

as_source_spectrum(t, *[, redshift, ...])

Build a SourceSpectrum giving 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()