Stationary

class legwork.source.Stationary(m_1, m_2, ecc, dist, n_proc=1, f_orb=None, a=None, position=None, polarisation=None, inclination=None, weights=None, gw_lum_tol=0.05, stat_tol=0.01, interpolate_g=True, interpolate_sc=True, sc_params={})[source]

Bases: Source

Subclass for sources that are stationary

Methods Summary

get_snr([t_obs, instrument, custom_psd, verbose])

Computes the SNR for a generic binary.

Methods Documentation

get_snr(t_obs=None, instrument=None, custom_psd=None, verbose=False)[source]

Computes the SNR for a generic binary. Also records the harmonic with maximum SNR for each binary in self.max_snr_harmonic.

Parameters
t_obsarray

Observation duration (default: value from sc_params)

instrument{{ ‘LISA’, ‘TianQin’, ‘custom’ }}

Instrument to observe with. If ‘custom’ then custom_psd must be supplied. (default: value from sc_params)

custom_psdfunction

Custom function for computing the PSD. Must take the same arguments as legwork.psd.lisa_psd() even if it ignores some. (default: function from sc_params)

Lfloat

LISA arm length in metres

approximate_Rboolean

Whether to approximate the response function (default: no)

confusion_noisevarious

Galactic confusion noise. Acceptable inputs are either one of the values listed in legwork.psd.get_confusion_noise(), “auto” (automatically selects confusion noise based on instrument - ‘robson19’ if LISA and ‘huang20’ if TianQin), or a custom function that gives the confusion noise at each frequency for a given mission length where it would be called by running noise(f, t_obs) and return a value with units of inverse Hertz

n_stepint

Number of time steps during observation duration

verboseboolean

Whether to print additional information to user

re_interpolate_scboolean

Whether to re-interpolate the sensitivity curve if the observation time or instrument changes. If False, warning will instead be given

which_sourcesboolean/array

Mask of which sources to calculate the SNR for. If None then calculate SNR for all sources.

Returns
SNRarray

The signal-to-noise ratio