Kavli Affiliate: Salvatore Vitale
| First 5 Authors: Noah E. Wolfe, Noah E. Wolfe, , ,
| Summary:
From catalogs of gravitational-wave transients, the population-level
properties of their sources and the formation channels of merging compact
binaries can be constrained. However, astrophysical conclusions can be biased
by misspecification or misestimation of the population likelihood. Despite
detection thresholds on the false-alarm rate (FAR) or signal-to-noise ratio
(SNR), the current catalog is likely contaminated by noise transients. Further,
computing the population likelihood becomes less accurate as the catalog grows.
Current methods to address these challenges often scale poorly with the number
of events and potentially become infeasible for future catalogs. Here, we
evaluate a simple remedy: increasing the significance threshold for including
events in population analyses. To determine the efficacy of this approach, we
analyze simulated catalogs of up to 1600 gravitational-wave signals from
black-hole mergers using full Bayesian parameter estimation with current
detector sensitivities. We show that the growth in statistical uncertainty
about the black-hole population, as we analyze fewer events but with higher
SNR, depends on the source parameters of interest. When the SNR threshold is
raised from 11 to 15 — reducing our catalog size by two–thirds — we find
that statistical uncertainties on the mass distribution only grow by a few 10%
and constraints on the spin distribution are essentially unchanged; meanwhile,
uncertainties on the high-redshift cosmic merger rate more than double.
Simultaneously, numerical uncertainty in the estimate of the population
likelihood more than halves, allowing us to ensure unbiased inference without
additional computational expense. Our results demonstrate that focusing on
higher-significance events is an effective way to facilitate robust
astrophysical inference with growing gravitational-wave catalogs.
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