uvex_transients.models.kilonovae.kne.KilonovaCoolingBlackbodySED.flux_band_log_cgs#

classmethod KilonovaCoolingBlackbodySED.flux_band_log_cgs(nu: NumericalInput, throughput: NumericalInput, t: NumericalInput, redshift: NumericalInput, luminosity_distance: NumericalInput, *, log_attenuation: NumericalInput | None = None, **parameters: CGSParameterValue) → FloatResult#

Natural log of the throughput-weighted mean flux density over a band, plain cgs numbers.

\[\log \bar{F}_\nu = \log \frac{\int F_\nu(\nu, t) \cdot T(\nu)\,d\nu}{\int T(\nu)\,d\nu}\]

using flux_cgs()’s (redshifted, distance-diluted) \(F_\nu\), integrated over the observed-frame frequency grid nu and bandpass response throughput by trapezoidal quadrature. Dividing by the integrated throughput keeps the result dimensionally a flux density, directly comparable to flux_cgs().

Because this method integrates away a frequency axis, t, redshift, luminosity_distance, and every parameter are each given one trailing axis internally so they broadcast against the nu grid; any shape you would otherwise pass unchanged to flux_log_cgs() still works here.

Parameters:

  • nu (array-like) – Observed frequency grid to integrate over, in Hz, shape (K,). Need not be sorted.

  • throughput (array-like) – Dimensionless bandpass response at each nu sample, shape (K,).

  • t (array-like) – Observed time since explosion, in seconds, any shape.

  • redshift (array-like) – Cosmological redshift, dimensionless, any shape.

  • luminosity_distance (array-like) – Luminosity distance, in cm, any shape.

  • log_attenuation (array-like, optional) – Natural log of an observed-frame multiplicative attenuation, sampled at the same nu grid (its last axis must have length K, in nu’s original, pre-sort order). Any leading axes broadcast against t/redshift/luminosity_distance/the parameters.

  • **parameters – This model’s parameter values, in cgs units, any shape.

Returns:

The natural log of \(\bar{F}_\nu\), in erg/s/cm^2/Hz, with the broadcast shape of t/redshift/luminosity_distance/ the parameters (the frequency axis is integrated away).

Return type:

numpy.ndarray