paper

Improved detection statistics for non Gaussian gravitational wave stochastic backgrounds

arXiv:2212.10038 · doi:10.1103/PhysRevD.107.124044

Abstract

In a recent paper we described a novel approach to the detection and parameter estimation of a non-Gaussian stochastic background of gravitational waves. In this work we propose an improved version of the detection procedure, preserving robustness against imperfect noise knowledge at no cost of detection performance: in the previous approach, the solution proposed to ensure robustness reduced the performances of the detection statistics, which in some cases (namely, mild non-Gaussianity) could be outperformed by Gaussian ones established in literature. We show, through a simple toy model, that the new detection statistic performs better than the previous one (and than the Gaussian statistic) everywhere in the parameter space. It approaches the optimal Neyman-Pearson statistics monotonically with increasing non-Gaussianity and/or number of detectors. In this study we discuss in detail its efficiency. This is a second, important step towards the implementation of a nearly--optimal detection procedure for a realistic non-Gaussian stochastic background. We discuss the relevance of results obtained in the context of the toy model used, and their importance for understanding a more realistic scenario.

12 pages, 5 figures (published on 23 June 2023)

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