Searches for stochastic gravitational-wave backgrounds

TL;DR

This paper reviews data analysis techniques for detecting a stochastic gravitational-wave background, focusing on cross-correlation methods and Bayesian approaches, without emphasizing specific astrophysical sources.

Contribution

It provides a comprehensive overview of methods used to search for stochastic gravitational-wave backgrounds, including new Bayesian techniques for binary black hole signals.

Findings

Effective cross-correlation methods for background detection

Extension to complex detector responses and overlap functions

Introduction of Bayesian search methods for binary black hole backgrounds

Abstract

These lecture notes provide a brief introduction to methods used to search for a stochastic background of gravitational radiation -- a superposition of gravitational-wave signals that are either too weak or too numerous to individually detect. The focus of these notes is on relevant data analysis techniques, not on the particular astrophysical or cosmological sources that are responsible for producing the background. The lecture notes are divided into two main parts: (i) an overview, consisting of a description of different types of gravitational-wave backgrounds and an introduction to the method of cross-correlating data from multiple detectors, which can be used to extract the signal from the noise; (ii) details, extending the previous discussion to non-trivial detector response, non-trivial overlap functions, and a recently proposed Bayesian method to search for the gravitational-wave background produced by stellar-mass binary black hole mergers throughout the universe. Suggested exercises for the reader are given throughout the text, and compiled in an appendix.