TypeIbSED

class uvex_transients.models.supernovae.Ibc.TypeIbSED(**overrides: Parameter | Quantity | float | int)

Type Ib supernova SED, with priors fit to a literature sample of stripped-envelope SNe.

Reuses ArnettDecaySED’s radioactive-decay Arnett diffusion and floored-photosphere blackbody entirely, exactly as TypeIaSED and TypeIcBLSED do; only _DEFAULT_PARAMETERS differs. The priors on M_Ni, M_ej and v_ej are the SN Ib subsample statistics (mean, sample standard deviation of the analytical-model fits in Table 6 of Lyman et al.[1], 13 events). kappa is fixed at \(0.06\,\mathrm{cm^2\,g^{-1}}\), the single grey optical opacity value Lyman et al. 2016 assume (rather than fit) for every event in their sample. kappa_gamma is fixed at \(0.04\,\mathrm{cm^2\,g^{-1}}\), comparable to TypeIaSED’s Scalzo+14-derived value (\(0.03\,\mathrm{cm^2\,g^{-1}}\)): Lyman et al. 2016’s own analytical model has no gamma-ray leakage term at all (it is the original Arnett 1982 diffusion formalism), so their table gives no direct constraint on it, and this package’s TypeIaSED value is used as the closest available analogue. T_floor is left close to TypeIaSED’s 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

[1]

J. D. Lyman, D. Bersier, P. A. James, P. A. Mazzali, J. J. Eldridge, M. Fraser, and E. Pian. Bolometric light curves and explosion parameters of 38 stripped-envelope core-collapse supernovae. Monthly Notices of the Royal Astronomical Society, 457:328–350, 2016. arXiv:1512.03422, doi:10.1093/mnras/stv2983.

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()