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On the use and interpretation of signal-model indistinguishability measures for gravitational-wave astronomy

On the use and interpretation of signal-model indistinguishability measures for gravitational-wave astronomy
On the use and interpretation of signal-model indistinguishability measures for gravitational-wave astronomy
The difference ("mismatch") between two gravitational-wave (GW) signals is often used to estimate the signal-to-noise ratio (SNR) at which they will be distinguishable in a measurement or, alternatively, when the errors in a signal model will lead to biased measurements. It is well known that the standard approach to calculate this "indistinguishability SNR" is too conservative: a model may fail the criterion at a given SNR, but not necessarily incur a biased measurement of any individual parameters. This problem can be solved by taking into account errors orthogonal to the model space (which therefore do not induce a bias), and calculating indistinguishability SNRs for individual parameters, rather than the full N-dimensional parameter space. We illustrate this approach with the simple example of aligned-spin binary-black-hole signals, and calculate accurate estimates of the SNR at which each parameter measurement will be biased. In general biases occur at much higher SNRs than predicted from the standard mismatch calculation. Which parameters are most easily biased depends sensitively on the details of a given waveform model, and the location in parameter space, and in some cases the bias SNR is as high as the conservative estimate. We also illustrate how the parameter bias SNR can be used to robustly specify waveform accuracy requirements for future detectors.
gravitational waves, black holes, systematics
arXiv
Thompson, Jonathan E.
9d28204d-0d18-45d7-925e-5fb111aa5908
Hoy, Charlie
7d31ecfa-4847-4904-85f3-ed04ba4c6bc3
Fauchon-Jones, Edward
d04a46a6-7d3a-4590-8d58-3d2171a63d37
Hannam, Mark
fdf732dc-e968-4b09-8262-7f4a0cb8f08e
Thompson, Jonathan E.
9d28204d-0d18-45d7-925e-5fb111aa5908
Hoy, Charlie
7d31ecfa-4847-4904-85f3-ed04ba4c6bc3
Fauchon-Jones, Edward
d04a46a6-7d3a-4590-8d58-3d2171a63d37
Hannam, Mark
fdf732dc-e968-4b09-8262-7f4a0cb8f08e

[Unknown type: UNSPECIFIED]

Record type: UNSPECIFIED

Abstract

The difference ("mismatch") between two gravitational-wave (GW) signals is often used to estimate the signal-to-noise ratio (SNR) at which they will be distinguishable in a measurement or, alternatively, when the errors in a signal model will lead to biased measurements. It is well known that the standard approach to calculate this "indistinguishability SNR" is too conservative: a model may fail the criterion at a given SNR, but not necessarily incur a biased measurement of any individual parameters. This problem can be solved by taking into account errors orthogonal to the model space (which therefore do not induce a bias), and calculating indistinguishability SNRs for individual parameters, rather than the full N-dimensional parameter space. We illustrate this approach with the simple example of aligned-spin binary-black-hole signals, and calculate accurate estimates of the SNR at which each parameter measurement will be biased. In general biases occur at much higher SNRs than predicted from the standard mismatch calculation. Which parameters are most easily biased depends sensitively on the details of a given waveform model, and the location in parameter space, and in some cases the bias SNR is as high as the conservative estimate. We also illustrate how the parameter bias SNR can be used to robustly specify waveform accuracy requirements for future detectors.

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2506.10530v1 - Author's Original
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Published date: 12 June 2025
Keywords: gravitational waves, black holes, systematics

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Local EPrints ID: 503216
URI: http://eprints.soton.ac.uk/id/eprint/503216
PURE UUID: 22dbf728-7fae-472d-9232-d2e8fe15ffb8
ORCID for Jonathan E. Thompson: ORCID iD orcid.org/0000-0002-0419-5517

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Date deposited: 24 Jul 2025 16:38
Last modified: 22 Aug 2025 02:44

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Contributors

Author: Jonathan E. Thompson ORCID iD
Author: Charlie Hoy
Author: Edward Fauchon-Jones
Author: Mark Hannam

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