Paper
Inspiral tests of general relativity and waveform geometry
Authors
Brian C. Seymour, Jacob Golomb, Yanbei Chen
Abstract
The phase evolution of gravitational waves encodes critical information about the orbital dynamics of binary systems. In this work, we test the robustness of parameterized tests against unmodeled deviations from general relativity. We demonstrate that these parameterized tests are flexible and sensitive in detecting generic deviations in the waveform using the Cutler-Vallisneri bias formalism. This universality arises from examining the inherent geometry of the waveform signal and understanding how biases manifest. We show how Bayes factors are governed by the intrinsic geometry of the waveform signal manifold when parameterized tests are used to approximate generic violations of GR. We use the singular value decomposition to propose templates that are orthogonal to parameterized tests, identifying degeneracies and enhancing the detection of potential deviations. More broadly, the geometric framework developed here clarifies -- at a fundamental level -- how subtle waveform effects (including orbital eccentricity, spin precession, waveform systematics, and instrumental glitches) can mimic one another in data, and when they are intrinsically distinguishable.
Metadata
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Raw Data (Debug)
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"raw_xml": "<entry>\n <id>http://arxiv.org/abs/2602.17524v1</id>\n <title>Inspiral tests of general relativity and waveform geometry</title>\n <updated>2026-02-19T16:36:52Z</updated>\n <link href='https://arxiv.org/abs/2602.17524v1' rel='alternate' type='text/html'/>\n <link href='https://arxiv.org/pdf/2602.17524v1' rel='related' title='pdf' type='application/pdf'/>\n <summary>The phase evolution of gravitational waves encodes critical information about the orbital dynamics of binary systems. In this work, we test the robustness of parameterized tests against unmodeled deviations from general relativity. We demonstrate that these parameterized tests are flexible and sensitive in detecting generic deviations in the waveform using the Cutler-Vallisneri bias formalism. This universality arises from examining the inherent geometry of the waveform signal and understanding how biases manifest. We show how Bayes factors are governed by the intrinsic geometry of the waveform signal manifold when parameterized tests are used to approximate generic violations of GR. We use the singular value decomposition to propose templates that are orthogonal to parameterized tests, identifying degeneracies and enhancing the detection of potential deviations. More broadly, the geometric framework developed here clarifies -- at a fundamental level -- how subtle waveform effects (including orbital eccentricity, spin precession, waveform systematics, and instrumental glitches) can mimic one another in data, and when they are intrinsically distinguishable.</summary>\n <category scheme='http://arxiv.org/schemas/atom' term='gr-qc'/>\n <published>2026-02-19T16:36:52Z</published>\n <arxiv:comment>17 pages, 11 figures, comments welcome</arxiv:comment>\n <arxiv:primary_category term='gr-qc'/>\n <author>\n <name>Brian C. Seymour</name>\n </author>\n <author>\n <name>Jacob Golomb</name>\n </author>\n <author>\n <name>Yanbei Chen</name>\n </author>\n </entry>"
}