SimInspiral¶

class igwn_ligolw.lsctables.SimInspiral(**kwargs)¶

Bases: RowType

Example:

>>> x = SimInspiral()
>>> x.ra_dec = 0., 0.
>>> x.ra_dec
(0.0, 0.0)
>>> x.ra_dec = None
>>> print(x.ra_dec)
None
>>> x.time_geocent = None
>>> print(x.time_geocent)
None
>>> print(x.end_time_gmst)
None
>>> x.time_geocent = LIGOTimeGPS(6e8)
>>> print(x.time_geocent)
600000000
>>> print(round(x.end_time_gmst, 8))
-2238.39417156
>>> x.distance = 100e6
>>> x.ra_dec = 0., 0.
>>> x.inclination = 0.
>>> x.coa_phase = 0.
>>> x.polarization = 0.
>>> x.snr_geometry_factors(("H1",))
{'H1': (0.490467233277456-0.4671010853697789j)}
>>> # NOTE:  complex, abs() is traditional value
>>> x.effective_distances(("H1",))
{'H1': (106915812.12292896+101822279.85362741j)}
>>> x.expected_snrs({"H1": 150e6})
{'H1': (5.885606799329472-5.605213024437346j)}

Attributes Summary

`alpha`
`alpha1`
`alpha2`
`alpha3`
`alpha4`
`alpha5`
`alpha6`
`amp_order`
`bandpass`
`beta`
`coa_phase`
`distance`
`eff_dist_g`
`eff_dist_h`
`eff_dist_l`
`eff_dist_t`
`eff_dist_v`
`end_time_gmst`
`eta`
`f_final`
`f_lower`
`g_end_time`
`g_end_time_ns`
`geocent_end_time`
`geocent_end_time_ns`
`h_end_time`
`h_end_time_ns`
`inclination`
`l_end_time`
`l_end_time_ns`
`latitude`
`longitude`
`mass1`
`mass2`
`mchirp`
`numrel_data`
`numrel_mode_max`
`numrel_mode_min`
`phi0`
`polarization`
`process_id`
`psi0`
`psi3`
`ra_dec`
`simulation_id`
`source`
`spin1`
`spin1x`
`spin1y`
`spin1z`
`spin2`
`spin2x`
`spin2y`
`spin2z`
`t_end_time`
`t_end_time_ns`
`taper`
`theta0`
`v_end_time`
`v_end_time_ns`
`waveform`

Methods Summary

`effective_distances`(instruments)	Compute and return a dictionary of the effective distances for this injection for the given instruments.
`expected_snrs`(horizon_distances)	Compute and return a dictionary of the expected complex SNRs for this injection in the given instruments.
`snr_geometry_factors`(instruments)	Compute and return a dictionary of the ratios of the source's physical distance to its effective distance for each of the given instruments.
`time_at_instrument`(instrument, offsetvector)	Return the "time" of the injection, delay corrected for the displacement from the geocentre to the given instrument.

Attributes Documentation

alpha¶

alpha1¶

alpha2¶

alpha3¶

alpha4¶

alpha5¶

alpha6¶

amp_order¶

bandpass¶

beta¶

coa_phase¶

distance¶

eff_dist_g¶

eff_dist_h¶

eff_dist_l¶

eff_dist_t¶

eff_dist_v¶

end_time_gmst¶

eta¶

f_final¶

f_lower¶

g_end_time¶

g_end_time_ns¶

geocent_end_time¶

geocent_end_time_ns¶

h_end_time¶

h_end_time_ns¶

inclination¶

l_end_time¶

l_end_time_ns¶

latitude¶

longitude¶

mass1¶

mass2¶

mchirp¶

numrel_data¶

numrel_mode_max¶

numrel_mode_min¶

phi0¶

polarization¶

process_id¶

psi0¶

psi3¶

ra_dec¶

simulation_id¶

source¶

spin1¶

spin1x¶

spin1y¶

spin1z¶

spin2¶

spin2x¶

spin2y¶

spin2z¶

t_end_time¶

t_end_time_ns¶

taper¶

theta0¶

time_geocent¶

v_end_time¶

v_end_time_ns¶

waveform¶

Methods Documentation

effective_distances(instruments)¶

Compute and return a dictionary of the effective distances for this injection for the given instruments. The effective distance is the distance at which an optimally oriented and positioned source would be seen with the same SNR as that with which this source will be seen in the given instrument. Effective distance is related to the physical distance, D, by the geometry factor

D_effective = D / (geometry factor).

NOTE that in this implementation the quantity returned is complex such that the expected complex SNR in a detector is

rho_{0} = 8 * D_horizon / D_effective

Traditionally the effective distance is a scalar and does not convey information about the phase of the signal-to-noise ratio. That quantity is the absolute value of the quantity computed by this method. The extension to complex values is done here to facilitate the use of this code in applications where the expected complex SNR is required.

See also .snr_geometry_factors(), .expected_snrs().

expected_snrs(horizon_distances)¶

Compute and return a dictionary of the expected complex SNRs for this injection in the given instruments. horizon_distances is a dictionary giving the horizon distance for each of the detectors for which an expected SNR is to be computed. The expected SNR in a detector is

rho_{0} = 8 * D_horizon / D_effective.

See also .effective_distances().

snr_geometry_factors(instruments)¶

Compute and return a dictionary of the ratios of the source’s physical distance to its effective distance for each of the given instruments. NOTE that the quantity returned is complex, where the magnitude of the value is that ratio and the phase is such that the expected complex SNR in a detector is given by

rho_{0} = 8 * (D_horizon / D) * snr_geometry_factor,

where D_horizon is the detector’s horizon distance for this waveform (computed from the detector’s noise spectral density), and D is the source’s physical distance. The geometry factor (what this method computes) depends on the direction to the source with respect to the antenna beam, the inclination of the source’s orbital plane, the wave frame’s polarization, and the phase of the waveform at the time of coalescence. The combination

D / geometry factor

is called the effective distance. See Equation (4.3) of arXiv:0705.1514.

See also .effective_distances(), .expected_snrs().

time_at_instrument(instrument, offsetvector)¶

Return the “time” of the injection, delay corrected for the displacement from the geocentre to the given instrument.

NOTE: this method does not account for the rotation of the Earth that occurs during the transit of the plane wave from the detector to the geocentre. That is, it is assumed the Earth is in the same orientation with respect to the celestial sphere when the wave passes through the detector as when it passes through the geocentre. The Earth rotates by about 1.5 urad during the 21 ms it takes light to travel the radius of the Earth, which corresponds to 10 m of displacement at the equator, or 33 light-ns. Therefore, the failure to do a proper retarded time calculation here results in errors as large as 33 ns. This is insignificant in present applications, but be aware that this approximation is being made if the return value is used in other contexts.