Mock data and science challenge for detecting an astrophysical stochastic gravitational-wave background with Advanced LIGO and Advanced Virgo

Duncan Meacher, Michael Coughlin, Sean Morris, Tania Regimbau, Nelson Christensen, Shivaraj Kandhasamy, Vuk Mandic, Joseph D. Romano, Eric Thrane

Research output: Contribution to journalArticlepeer-review

46 Scopus citations

Abstract

The purpose of this mock data and science challenge is to prepare the data analysis and science interpretation for the second generation of gravitational-wave experiments Advanced LIGO-Virgo in the search for a stochastic gravitational-wave background signal of astrophysical origin. Here we present a series of signal and data challenges, with increasing complexity, whose aim is to test the ability of current data analysis pipelines at detecting an astrophysically produced gravitational-wave background, test parameter estimation methods and interpret the results. We introduce the production of these mock data sets that includes a realistic observing scenario data set where we account for different sensitivities of the advanced detectors as they are continuously upgraded toward their design sensitivity. After analyzing these with the standard isotropic cross-correlation pipeline we find that we are able to recover the injected gravitational-wave background energy density to within 2σ for all of the data sets and present the results from the parameter estimation. The results from this mock data and science challenge show that advanced LIGO and Virgo will be ready and able to make a detection of an astrophysical gravitational-wave background within a few years of operations of the advanced detectors, given a high enough rate of compact binary coalescing events.

Original languageEnglish (US)
Article number063002
JournalPhysical Review D - Particles, Fields, Gravitation and Cosmology
Volume92
Issue number6
DOIs
StatePublished - Sep 2 2015

Bibliographical note

Publisher Copyright:
© 2015 American Physical Society.

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