Identifying biases from terrestrial noise artifacts in GW parameter inference
ORAL
Abstract
Terrestrial noise artifacts ("glitches") can bias the inference of gravitational wave (GW) source properties, especially for properties which have only subtle effects on the morphology of the signal, such as the spins of the compact objects. Distinct features, often time and/or frequency dependent, will typically arise when using GW signal models to fit data which is impacted by a glitch, and these features are exploited by search algorithms to identify false candidates. However, corresponding tests are currently lacking for parameter estimation, which prevents us from evaluating whether glitch mitigation methods have successfully eliminated biases. We present a number of tests which address this deficiency, discuss the relative merits and applications of each, and present results from their application in various cases.
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Presenters
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Rhiannon P Udall
LIGO Laboratory, Caltech
Authors
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Rhiannon P Udall
LIGO Laboratory, Caltech
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Derek Davis
LIGO Laboratory, Caltech
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Sena Kalabalık
Bogazici University
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Simona J Miller
LIGO Laboratory, Caltech
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Sophie R Hourihane
Caltech
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Lucy Thomas
LIGO Laboratory, Caltech