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Measuring angular N-point correlations of binary black-hole merger gravitational-wave events with hierarchical Bayesian inference | | Sharan Banagiri
; Vuk Mandic
; Claudia Scarlata
; Kate Z. Yang
; | | Date: |
1 Jun 2020 | | Abstract: | Advanced LIGO and Virgo have detected ten binary black-hole mergers by the
end of their second observing run. These mergers have already allowed
constraints to be placed on the population distribution of black-holes in the
Universe, which will only improve with more detections and increasing
sensitivity of the detectors. In this paper we develop techniques to measure
the angular distribution of black-hole mergers by measuring their statistical
$N$-point correlations through hierarchical Bayesian inference. We apply it to
the special case of two-point angular correlations using a Legendre polynomial
basis on the sky. Building on the mixture model formalism introduced in Ref.[1]
we show how one can measure two-point correlations with no threshold on
significance, allowing us to target the ensemble of sub-threshold binary-black
hole mergers not resolvable with the current generation of ground based
detectors. We also show how one can use these methods to correlate
gravitational-waves with other probes of large scale angular structure like
galaxy counts, and validate both techniques through simulations. | | Source: | arXiv, 2006.0633 | | Services: | Forum | Review | PDF | Favorites | |
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