LFBOTCoolingBlackbodySED#

class uvex_transients.models.lfbots.lfbots.LFBOTCoolingBlackbodySED(**overrides: Parameter | Quantity | float | int)[source]#

A Gaussian-rise/power-law-decline light curve with a Villar-type cooling blackbody photosphere.

This model pairs GaussianRisePowerLawLightcurve with a time-dependent blackbody spectral shape,

\[L_\nu(\nu, t) = L_\mathrm{bol}(t)\, S_\mathrm{BB}\!\left[\nu, T(t)\right],\]

where \(S_\mathrm{BB}\) is the normalized blackbody spectrum provided by BlackbodySpectrum. The photosphere follows the same cooling-law form as VillarCoolingBlackbodySED, but with the cooling timescale fixed to the light curve’s own \(t_\mathrm{peak}\) rather than a separate free parameter,

\[T(t) = T_\mathrm{floor} + (T_0 - T_\mathrm{floor})(1 + t/t_\mathrm{peak})^{-\alpha_T},\]

which has the correct \(T \to T_\mathrm{floor} + (T_0 - T_\mathrm{floor})(t/t_\mathrm{peak})^{-\alpha_T}\) power-law asymptote at late times.

Parameters

The model parameters are summarized below.

Parameter	Symbol	Description
`amplitude`	\(A\)	Peak bolometric luminosity.
`t_peak`	\(t_\mathrm{peak}\)	Time of peak luminosity since explosion.
`decline_index`	\(\alpha_\mathrm{decline}\)	Positive post-peak power-law decline index of the bolometric light curve.
`T0`	\(T_0\)	Photospheric temperature at t=0 (the T(t) -> T0 limit, not literally T at peak).
`T_floor`	\(T_\mathrm{floor}\)	Asymptotic late-time photospheric temperature (T(t) -> T_floor as t -> infinity).
`alpha_T`	\(\alpha_T\)	Late-time photospheric cooling power-law index.

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`()