TY - JOUR
T1 - Detection methods for stochastic gravitational-wave backgrounds
T2 - A unified treatment
AU - Romano, Joseph D.
AU - Cornish, Neil J.
N1 - Publisher Copyright:
© The Author(s) 2017.
PY - 2017/12
Y1 - 2017/12
N2 - We review detection methods that are currently in use or have been proposed to search for a stochastic background of gravitational radiation. We consider both Bayesian and frequentist searches using ground-based and space-based laser interferometers, spacecraft Doppler tracking, and pulsar timing arrays; and we allow for anisotropy, non-Gaussianity, and non-standard polarization states. Our focus is on relevant data analysis issues, and not on the particular astrophysical or early Universe sources that might give rise to such backgrounds. We provide a unified treatment of these searches at the level of detector response functions, detection sensitivity curves, and, more generally, at the level of the likelihood function, since the choice of signal and noise models and prior probability distributions are actually what define the search. Pedagogical examples are given whenever possible to compare and contrast different approaches.We have tried to make the article as self-contained and comprehensive as possible, targeting graduate students and new researchers looking to enter this field.
AB - We review detection methods that are currently in use or have been proposed to search for a stochastic background of gravitational radiation. We consider both Bayesian and frequentist searches using ground-based and space-based laser interferometers, spacecraft Doppler tracking, and pulsar timing arrays; and we allow for anisotropy, non-Gaussianity, and non-standard polarization states. Our focus is on relevant data analysis issues, and not on the particular astrophysical or early Universe sources that might give rise to such backgrounds. We provide a unified treatment of these searches at the level of detector response functions, detection sensitivity curves, and, more generally, at the level of the likelihood function, since the choice of signal and noise models and prior probability distributions are actually what define the search. Pedagogical examples are given whenever possible to compare and contrast different approaches.We have tried to make the article as self-contained and comprehensive as possible, targeting graduate students and new researchers looking to enter this field.
KW - Data analysis
KW - Gravitational waves
KW - Stochastic backgrounds
UR - http://www.scopus.com/inward/record.url?scp=85017442672&partnerID=8YFLogxK
U2 - 10.1007/s41114-017-0004-1
DO - 10.1007/s41114-017-0004-1
M3 - Review article
AN - SCOPUS:85017442672
SN - 2367-3613
VL - 20
SP - 1
EP - 223
JO - Living Reviews in Relativity
JF - Living Reviews in Relativity
IS - 1
M1 - 2
ER -