Gravitational-wave Parameter Estimation in Non-Gaussian Noise Using Score-based Likelihood Characterization

Gravitational-wave Parameter Estimation in Non-Gaussian Noise Using Score-based Likelihood Characterization

Gravitational-wave (GW) parameter estimation typically assumes that instrumental noise is Gaussian and stationary. Obvious departures from this idealization are typically handled on a case-by-case basis, e.g., through bespoke procedures to “clean” non-Gaussian noise transients (glitches), as was fam...

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Bibliographic Details
Main Authors: Ronan Legin, Maximiliano Isi, Kaze W. K. Wong, Yashar Hezaveh, Laurence Perreault-Levasseur
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:The Astrophysical Journal Letters
Subjects:
LIGO
Non-Gaussianity
Bayesian statistics
Gravitational waves
Neural networks
Posterior distribution
Online Access:https://doi.org/10.3847/2041-8213/add681
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https://doi.org/10.3847/2041-8213/add681

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