snr_circ_evolving

legwork.snr.snr_circ_evolving(m_1, m_2, f_orb_i, dist, t_obs, n_step, t_merge=None, interpolated_g=None, interpolated_sc=None, **kwargs)

Computes SNR for circular and stationary sources

Parameters

m_1float/array

Primary mass

m_2float/array

Secondary mass

f_orb_ifloat/array

Initial orbital frequency

distfloat/array

Distance to the source

t_obsfloat

Total duration of the observation

n_stepint

Number of time steps during observation duration

t_mergefloat/array

Time until merger

interpolated_gfunction

A function returned by scipy.interpolate.interp2d that computes g(n,e) from Peters (1964). The code assumes that the function returns the output sorted as with the interp2d returned functions (and thus unsorts). Default is None and uses exact g(n,e) in this case.

interpolated_scfunction

A function returned by scipy.interpolate.interp1d that computes the LISA sensitivity curve. Default is None and uses exact values. Note: take care to ensure that your interpolated function has the same LISA observation time as t_obs and uses the same instrument.

**kwargsvarious

Keyword args are passed to legwork.psd.power_spectral_density(), see those docs for details on possible arguments.

Returns

snfloat/array

SNR for each binary