inspiral_range¶

gwpy.astro.inspiral_range(psd: FrequencySeries, snr: float = 8, mass1: float = 1.4, mass2: float = 1.4, fmin: float | None = None, fmax: float | None = None, horizon: bool = False, **kwargs) → Quantity[source]¶

Calculate the cosmology-corrected inspiral sensitive distance.

This method returns the distance (in megaparsecs) to which a compact binary inspiral with the given component masses would be detectable given the instrumental PSD. The calculation is defined in Belczynski et. al (2014):

https://dx.doi.org/10.1088/0004-637x/789/2/120

Parameters:

psdFrequencySeries: The instrumental power-spectral-density data.
snrfloat, optional: The signal-to-noise ratio for which to calculate range.
mass1float, Quantity, optional: The mass of the first binary component (float assumed in solar masses).
mass2float, Quantity, optional: The mass of the second binary component (float assumed in solar masses).
fminfloat, optional: The lower frequency cut-off of the integral, default: psd.df.
fmaxfloat, optional: The maximum frequency limit of the integral, defaults to the rest-frame innermost stable circular orbit (ISCO) frequency.
horizonbool, optional: If True, return the maximal ‘horizon’ luminosity distance, otherwise return the angle-averaged comoving distance.
**kwargs: Additional keyword arguments to CBCWaveform.

Returns:

rangeQuantity: The calculated inspiral range [Mpc].

See also

sensemon_range: For the method based on LIGO-T030276, also known as LIGO SenseMonitor.
inspiral-range: The package which does heavy lifting for waveform simulation and cosmology calculations.

Examples

Grab some data for LIGO-Livingston around GW150914 and generate a PSD:

>>> from gwpy.timeseries import TimeSeries
>>> hoft = TimeSeries.fetch_open_data("H1", 1126259446, 1126259478)
>>> hoff = hoft.psd(fftlength=4)

Now, we can calculate the inspiral_range():

>>> from gwpy.astro import inspiral_range
>>> r = inspiral_range(hoff, fmin: float = 30)
>>> print(r)
70.4612102889 Mpc