ArnettMagnetarSpindownSED#

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

Magnetar spin-down powered SED, with the light curve from Arnett-style diffusion.

This model follows the formalism of Nicholl et al.[1] (the MOSFiT magnetar model of Type I superluminous supernovae) and the leakage treatment of Wang et al.[2].

A newly born magnetar injects

\[F_\mathrm{mag}(t) = \frac{E_\mathrm{mag}/t_\mathrm{mag}}\frac{1}{(1 + t/t_\mathrm{mag})^{2}}\]

into homologously expanding, grey-opacity ejecta, which diffuses out and leaks high-energy photons according to compute_arnett_luminosity().

The temperature is computed using a floored photospheric temperature model:

\[T(t) = \max\left\{\left[\frac{L(t)}{4\pi\sigma_\mathrm{SB}(v_\mathrm{ej}t)^2}\right]^{1/4}, T_\mathrm{floor}\right\}, \qquad L_\nu(\nu, t) = L(t)\,\frac{\pi B_\nu(\nu, T(t))}{\sigma_\mathrm{SB}T(t)^4}.\]

The light curve \(L(t)\) is integrated once per evaluation and reused for both the temperature and the spectral luminosity.

Parameters

Parameter	Symbol	Description
`spin_period`	\(P\)	Initial magnetar spin period.
`B_perp`	\(B_\perp\)	Perpendicular component of the dipole field, in Gaussian-cgs gauss (`GAUSS_CGS`).
`M_ej`	\(M_\mathrm{ej}\)	Ejecta mass.
`v_ej`	\(v_\mathrm{ej}\)	Ejecta velocity, taken to be constant and equal to the photospheric velocity.
`M_ns`	\(M_\mathrm{NS}\)	Neutron star mass.
`kappa`	\(\kappa\)	Grey optical opacity.
`kappa_gamma`	\(\kappa_\gamma\)	Opacity to high-energy photons; sets how much of the late-time input energy leaks out.
`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`()