inspiral_range

gwpy.astro.inspiral_range(psd, snr=8, mass1=1.4, mass2=1.4, fmin=None, fmax=None, horizon=False, **kwargs)[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, default: 8

mass1float, Quantity, optional

the mass (float assumed in solar masses) of the first binary component, default: 1.4

mass2float, Quantity, optional

the mass (float assumed in solar masses) of the second binary component, default: 1.4

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, default: False

**kwargsdict, optional

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=30)
>>> print(r)
70.4612102889 Mpc