PowerLawLightcurve

class uvex_transients.models.lightcurves.generic.PowerLawLightcurve(**overrides: Parameter | Quantity | float | int)

A power-law decline beginning at a reference time.

\[\begin{split}L(t) = \begin{cases} 0, & t < t_\mathrm{ref}, \\[4pt] A \left(\dfrac{t}{t_\mathrm{ref}}\right)^{-\alpha}, & t \ge t_\mathrm{ref}. \end{cases}\end{split}\]

The luminosity is therefore exactly \(A\) at t_ref. This form is useful for generic afterglows and other transients whose post-onset emission is approximately scale free.

Restricting the model to t >= t_ref avoids the formal divergence of a declining power law as \(t \rightarrow 0\).

Parameters

The light curve parameters are summarized below.

Parameter	Symbol	Description
amplitude	\(A\)	Luminosity at the reference time.
t_ref	\(t_\mathrm{ref}\)	Reference time at which the power law begins.
index	\(\alpha\)	Positive power-law decline index.

Methods

eval(t, **parameters)	Evaluate the bolometric luminosity at the given time.
eval_cgs(t, **parameters)	Bolometric luminosity, taking and returning plain cgs numbers.
eval_from_arrays(t, *parameters)	Positional-argument form of eval().
eval_log(t, **parameters)	Natural log of the bolometric luminosity, given physical-unit inputs.
eval_log_cgs(t, **parameters)	Natural log of the bolometric luminosity, taking and returning plain cgs numbers.
get(k[,d])
items()
keys()
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(t[, size, rng])	Draw random parameter realizations and evaluate the model at the given time.
unpack_params_from_arrays(*parameters)	Convert an ordered sequence of parameter values back into a dict.
values()