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Counting And Confusion: Bayesian Rate Estimation With Multiple Populations

5 Pith papers cite this work. Polarity classification is still indexing.

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abstract

We show how to obtain a Bayesian estimate of the rates or numbers of signal and background events from a set of events when the shapes of the signal and background distributions are known, can be estimated, or approximated; our method works well even if the foreground and background event distributions overlap significantly and the nature of any individual event cannot be determined with any certainty. We give examples of determining the rates of gravitational-wave events in the presence of background triggers from a template bank when noise parameters are known and/or can be fit from the trigger data. We also give an example of determining globular-cluster shape, location, and density from an observation of a stellar field that contains a non-uniform background density of stars superimposed on the cluster stars.

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GstLAL O4 Online Results Paper

gr-qc · 2026-05-18 · unverdicted · novelty 3.0

GstLAL produced low-latency alerts for 250 astrophysically plausible gravitational-wave candidates during O4, providing the first upload for 222 and the sole upload for 75, with 88 percent of significant catalog events detected and 93 percent classification agreement.

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