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On combining information from multiple gravitational wave sources

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

7 Pith papers citing it
abstract

In the coming years, advanced gravitational wave detectors will observe signals from a large number of compact binary coalescences. The majority of these signals will be relatively weak, making the precision measurement of subtle effects, such as deviations from general relativity, challenging in the individual events. However, many weak observations can be combined into precise inferences, if information from the individual signals is combined in an appropriate way. In this study we revisit common methods for combining multiple gravitational wave observations to test general relativity, namely (i) multiplying the individual likelihoods of beyond-general-relativity parameters and (ii) multiplying the Bayes Factor in favor of general relativity from each event. We discuss both methods and show that they make stringent assumptions about the modified theory of gravity they test. In particular, the former assumes that all events share the same beyond-general-relativity parameter, while the latter assumes that the theory of gravity has a new unrelated parameter for each detection. We show that each method can fail to detect deviations from general relativity when the modified theory being tested violates these assumptions. We argue that these two methods are the extreme limits of a more generic framework of hierarchical inference on hyperparameters that characterize the underlying distribution of single-event parameters. We illustrate our conclusions first using a simple model of Gaussian likelihoods, and also by applying parameter estimation techniques to a simulated dataset of gravitational waveforms in a model where the graviton is massive. We argue that combining information from multiple sources requires explicit assumptions that make the results inherently model-dependent.

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background 2 dataset 1 method 1

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gr-qc 7

representative citing papers

Testing General Relativity with GWTC-4.0 through mixture models

gr-qc · 2026-07-08 · conditional · novelty 6.0

A mixture-model framework for combining gravitational-wave tests of General Relativity yields Bayes factors of 10-20 favoring GR, substantially lower than existing methods that assume uniform deviations across events.

Constraining Gravitational Wave Memory with Hierarchical Inference

gr-qc · 2026-05-26 · unverdicted · novelty 5.0

Hierarchical Bayesian inference on GWTC-5.0 constrains the memory enhancement factor to 0.26 with large uncertainties consistent with the GR value of 1 and forecasts that 2000 detections are needed for a 1σ constraint away from zero.

Tests of General Relativity with GWTC-3

gr-qc · 2021-12-13 · accept · novelty 3.0

No evidence for physics beyond general relativity is found in the analysis of 15 GW events from GWTC-3, with consistency in residuals, PN parameters, and remnant properties.

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Showing 7 of 7 citing papers.