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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.

Presenters

  • Rhiannon P Udall

    LIGO Laboratory, Caltech

Authors

  • Rhiannon P Udall

    LIGO Laboratory, Caltech

  • Derek Davis

    LIGO Laboratory, Caltech

  • Sena Kalabalık

    Bogazici University

  • Simona J Miller

    LIGO Laboratory, Caltech

  • Sophie R Hourihane

    Caltech

  • Lucy Thomas

    LIGO Laboratory, Caltech