Published May 15, 2024 | Version Published
Journal Article Open

Unbiased estimation of gravitational-wave anisotropies from noisy data

Abstract

One of the most exciting targets of current and future gravitational-wave observations is the angular power spectrum of the astrophysical GW background. This cumulative signal encodes information about the large-scale structure of the Universe, as well as the formation and evolution of compact binaries throughout cosmic time. However, the finite rate of compact binary mergers gives rise to temporal shot noise, which introduces a significant bias in measurements of the angular power spectrum if not explicitly accounted for. Previous work showed that this bias can be removed by cross-correlating GW sky maps constructed from different observing times. However, this work considered an idealized measurement scenario, ignoring detector specifics and in particular noise contributions. Here we extend this temporal cross-correlation method to account for these difficulties, allowing us to implement the first unbiased anisotropic search pipeline for LIGO-Virgo-KAGRA data. In doing so, we show that the existing pipeline is biased even in the absence of shot noise, due to previously neglected subleading contributions to the noise covariance. We apply our pipeline to mock LIGO data, and find that our improved analysis will be crucial for stochastic searches from the current observing run (O4) onwards.

Copyright and License

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

Acknowledgement

We would like to thank Shivaraj Kandhasamy for carefully reviewing this manuscript (LIGO-Document No. P2300434) as a part of the LVK Collaboration’s internal review process. This material is based upon work supported by NSF’s LIGO Laboratory, which is a major facility fully funded by the National Science Foundation. The authors acknowledge computational resources provided by the LIGO Laboratory and supported by NSF Grants No. PHY-0757058 and No. PHY-0823459. We thank Deepali Agarwal and Stavros Venikoudis for useful comments, and in particular Jishnu Suresh for many useful discussions on how to run pystoch. N. K. is supported by King’s College London through an NMES Funded Studentship. A. C. J. is supported by the Science and Technology Facilities Council (STFC) through the UKRI Quantum Technologies for Fundamental Physics Programme [Grant No. ST/T005904/1]. 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. J. D. R. acknowledges support from National Science Foundation (NSF) Grant No. PHY-2207270. M. S. acknowledges support from the Science and Technology Facility Council (STFC), UK, under the research Grant No. ST/X000753/1. This work was partly enabled by the UCL Cosmoparticle Initiative.

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Additional details

Identifiers

ISSN
2470-0029

Funding

LIGO Scientific Collaboration
National Science Foundation
PHY-0757058
National Science Foundation
PHY-0823459
King's College London
Science and Technology Facilities Council
ST/X000753/1
European Research Council
Marie Skłodowska-Curie Fellowship 101064542
National Science Foundation
PHY-1912594
National Science Foundation
PHY-2207270
Science and Technology Facilities Council
ST/T005904/1

Caltech Custom Metadata

Caltech groups
LIGO
Other Numbering System Name
LIGO Document
Other Numbering System Identifier
P2300434