SimCBC

class igwn_ligolw.lsctables.SimCBC(**kwargs)

Bases: RowType

Example: >>> x = SimCBC() >>> 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 >>> x.time_geocent = LIGOTimeGPS(6e8) >>> print(x.time_geocent) 600000000 >>> x.d_lum = 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

alphappe

alphappe0

alphappe1

alphappe2

alphappe3

alphappe4

alphappe5

alphappe6

alphappe7

ampinterpol

ampo

axis

betappe

betappe0

betappe1

betappe2

betappe3

betappe4

betappe5

betappe6

betappe7

cbc_model

cbc_sim_id

coa_phase

convention

d_lum

dalpha1

dalpha2

dalpha3

dalpha4

dalpha5

dbeta1

dbeta2

dbeta3

dchi0

dchi1

dchi2

dchi3

dchi4

dchi5

dchi5l

dchi6

dchi6l

dchi7

dec

dquadmon1

dquadmon2

dsigma1

dsigma2

dsigma3

dsigma4

dxi1

dxi2

dxi3

dxi4

dxi5

dxi6

eccentricity

ecco

eobchoosenumoranalhamder

eobellmaxfornyquistcheck

expansionorder

f22_ref_spin

f22_start

f_ecc

fend

finalspinmod

geocent_end_time

geocent_end_time_ns

getideo

gmtideo

h_snr

inclination

insampfitsversion

insamphmversion

insampversion

insphasehmversion

insphaseversion

inspiralversion

intampfitsversion

intamphmversion

intampversion

intphasehmversion

intphaseversion

k_snr

l_snr

lambda1

lambda2

liv

liv_a_sign

log10lambda_eff

longascnodes

lscorr

mass1_det

mass2_det

mbandprecversion

meanperano

mergerversion

modearray

modearrayjframe

modes

modesl0frame

nltidesa1

nltidesa2

nltidesf1

nltidesf2

nltidesn1

nltidesn2

nongr_alpha

numreldata

phaseo

phaseref21

phi1

phi2

phi3

phi4

polarization

precmodes

precthresholdmband

precversion

process_id

ra

ra_dec

rdampfitsversion

rdamphmversion

rdampversion

rdphasehmversion

rdphaseversion

redshift

sideband

spin1

spin1x

spin1y

spin1z

spin2

spin2x

spin2y

spin2z

spino

thresholdmband

tidalhexadecapolarlambda1

tidalhexadecapolarlambda2

tidaloctupolarfmode1

tidaloctupolarfmode2

tidaloctupolarlambda1

tidaloctupolarlambda2

tidalquadrupolarfmode1

tidalquadrupolarfmode2

tideo

time_slide_id

transprecessionmethod

twistphenomhm

usemodes

v_snr

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

alphappe
alphappe0
alphappe1
alphappe2
alphappe3
alphappe4
alphappe5
alphappe6
alphappe7
ampinterpol
ampo
axis
betappe
betappe0
betappe1
betappe2
betappe3
betappe4
betappe5
betappe6
betappe7
cbc_model
cbc_sim_id
coa_phase
convention
d_lum
dalpha1
dalpha2
dalpha3
dalpha4
dalpha5
dbeta1
dbeta2
dbeta3
dchi0
dchi1
dchi2
dchi3
dchi4
dchi5
dchi5l
dchi6
dchi6l
dchi7
dec
dquadmon1
dquadmon2
dsigma1
dsigma2
dsigma3
dsigma4
dxi1
dxi2
dxi3
dxi4
dxi5
dxi6
eccentricity
ecco
eobchoosenumoranalhamder
eobellmaxfornyquistcheck
expansionorder
f22_ref_spin
f22_start
f_ecc
fend
finalspinmod
geocent_end_time
geocent_end_time_ns
getideo
gmtideo
h_snr
inclination
insampfitsversion
insamphmversion
insampversion
insphasehmversion
insphaseversion
inspiralversion
intampfitsversion
intamphmversion
intampversion
intphasehmversion
intphaseversion
k_snr
l_snr
lambda1
lambda2
liv
liv_a_sign
log10lambda_eff
longascnodes
lscorr
mass1_det
mass2_det
mbandprecversion
meanperano
mergerversion
modearray
modearrayjframe
modes
modesl0frame
nltidesa1
nltidesa2
nltidesf1
nltidesf2
nltidesn1
nltidesn2
nongr_alpha
numreldata
phaseo
phaseref21
phi1
phi2
phi3
phi4
polarization
precmodes
precthresholdmband
precversion
process_id
ra
ra_dec
rdampfitsversion
rdamphmversion
rdampversion
rdphasehmversion
rdphaseversion
redshift
sideband
spin1
spin1x
spin1y
spin1z
spin2
spin2x
spin2y
spin2z
spino
thresholdmband
tidalhexadecapolarlambda1
tidalhexadecapolarlambda2
tidaloctupolarfmode1
tidaloctupolarfmode2
tidaloctupolarlambda1
tidaloctupolarlambda2
tidalquadrupolarfmode1
tidalquadrupolarfmode2
tideo
time_geocent
time_slide_id
transprecessionmethod
twistphenomhm
usemodes
v_snr

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.