Published July 15, 2024 | Version Published
Journal Article Open

Background information: A study on the sensitivity of astrophysical gravitational-wave background searches

  • 1. ROR icon California Institute of Technology
  • 2. ROR icon University of Milano-Bicocca
  • 3. ROR icon INFN Sezione di Milano Bicocca
  • 4. ROR icon University of Chicago
  • 5. ROR icon Stony Brook University

Abstract

The vast majority of gravitational-wave signals from stellar-mass compact binary mergers are too weak to be individually detected with present-day instruments and instead contribute to a faint, persistent background. This astrophysical background is targeted by searches that model the gravitational-wave ensemble collectively with a small set of parameters. The traditional search models the background as a stochastic field and estimates its amplitude by cross-correlating data from multiple interferometers. A different search uses gravitational-wave templates to marginalize over all individual event parameters and measure the duty cycle and population properties of binary mergers. Both searches ultimately estimate the total merger rate of compact binaries and are expected to yield a detection in the coming years. Given the conceptual and methodological differences between them, though, it is not well understood how their results should be mutually interpreted. In particular, when a detection of an astrophysical compact binary background is claimed by either approach, which portion of the population is in fact contributing to this detection? In this paper, we use the Fisher information to study the implications of a background detection in terms of which region of the Universe each approach probes. Specifically, we quantify how information about the compact binary merger rate is accumulated by each search as a function of the event redshift. For the LIGO design sensitivity and a uniform-in-comoving-volume distribution of equal-mass 30⁢𝑀⊙ binaries, the traditional cross-correlation search obtains 99% of its information from binaries up to redshift 2.5 (average signal-to-noise ratio <8), and the template-based search from binaries up to redshift 1.0 (average signal-to-noise ratio ∼8). While we do not calculate the total information accumulated by each search, our analysis emphasizes the need to pair any claimed detection of the stochastic background with an assessment of which binaries contribute to said detection. In the process, we also clarify the astrophysical assumptions imposed by each search.

Copyright and License

© 2024 American Physical Society.

Acknowledgement

We thank Michele Vallisneri for useful discussions. A. I. R. is supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 101064542, and acknowledges support from the NSF Award No. PHY-1912594. T. C. is supported by the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship, a Schmidt Futures program. K. C. acknowledges support from NSF Grant No. PHY-2110111 and the Sloan Foundation. W. F. is supported in part by the Simons Foundation. The authors are grateful for computational resources provided by the LIGO Laboratory and supported by National Science Foundation Grants No. PHY-0757058 and No. PHY-0823459. 

Software References

Software packages employed: numpy [44], scipy [45], gwpy [46], bilby [41], matplotlib [47], seaborn [48].

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Additional details

Identifiers

ISSN
2470-0029

Funding

European Research Council
Marie Skłodowska-Curie Fellowship 101064542
National Science Foundation
PHY-1912594
National Science Foundation
PHY-2110111
National Science Foundation
PHY-0757058
National Science Foundation
PHY-0823459
Alfred P. Sloan Foundation
Schmidt Family Foundation
Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship
Simons Foundation

Caltech Custom Metadata

Caltech groups
TAPIR, Astronomy Department, Walter Burke Institute for Theoretical Physics, LIGO