Assessing and Mitigating the Impact of Glitches on Gravitational-Wave Parameter Estimation: a Model Agnostic Approach

Fuente: arXiv
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Autores principales: Ghonge, Sudarshan, Brandt, Joshua, Sullivan, J. M., Millhouse, Margaret, Chatziioannou, Katerina, Clark, James A., Littenberg, Tyson, Cornish, Neil, Hourihane, Sophie, Cadonati, Laura
Formato: Preprint
Publicado: 2023
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author Ghonge, Sudarshan
Brandt, Joshua
Sullivan, J. M.
Millhouse, Margaret
Chatziioannou, Katerina
Clark, James A.
Littenberg, Tyson
Cornish, Neil
Hourihane, Sophie
Cadonati, Laura
author_facet Ghonge, Sudarshan
Brandt, Joshua
Sullivan, J. M.
Millhouse, Margaret
Chatziioannou, Katerina
Clark, James A.
Littenberg, Tyson
Cornish, Neil
Hourihane, Sophie
Cadonati, Laura
contents In this paper we investigate the impact of transient noise artifacts, or {\it glitches}, on gravitational-wave inference from ground-based interferometer data, and test how modeling and subtracting these glitches affects the inferred parameters. Due to their time-frequency morphology, broadband glitches cause moderate to significant biasing of posterior distributions away from true values. In contrast, narrowband glitches induce negligible biasing effects, due to distinct signal and glitch morphologies. We inject simulated binary black hole signals into data containing three occurring glitch types from past LIGO-Virgo observing runs, and reconstruct both signal and glitch waveforms using \bw{}, a wavelet-based Bayesian analysis. We apply the standard LIGO-Virgo-KAGRA deglitching procedure to the detector data, which consists of subtracting from calibrated LIGO data the glitch waveform estimated by the joint \bw{} inference. {We produce posterior distributions on the parameters of the injected signal before and after subtracting the glitch,} and we {show that removing the transient noise} effectively mitigates bias from broadband glitches. This study provides a baseline validation of existing techniques, while demonstrating waveform reconstruction improvements to the Bayesian algorithm for robust astrophysical characterization in glitch-prone detector data.
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id arxiv_https___arxiv_org_abs_2311_09159
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Assessing and Mitigating the Impact of Glitches on Gravitational-Wave Parameter Estimation: a Model Agnostic Approach
Ghonge, Sudarshan
Brandt, Joshua
Sullivan, J. M.
Millhouse, Margaret
Chatziioannou, Katerina
Clark, James A.
Littenberg, Tyson
Cornish, Neil
Hourihane, Sophie
Cadonati, Laura
General Relativity and Quantum Cosmology
Instrumentation and Methods for Astrophysics
In this paper we investigate the impact of transient noise artifacts, or {\it glitches}, on gravitational-wave inference from ground-based interferometer data, and test how modeling and subtracting these glitches affects the inferred parameters. Due to their time-frequency morphology, broadband glitches cause moderate to significant biasing of posterior distributions away from true values. In contrast, narrowband glitches induce negligible biasing effects, due to distinct signal and glitch morphologies. We inject simulated binary black hole signals into data containing three occurring glitch types from past LIGO-Virgo observing runs, and reconstruct both signal and glitch waveforms using \bw{}, a wavelet-based Bayesian analysis. We apply the standard LIGO-Virgo-KAGRA deglitching procedure to the detector data, which consists of subtracting from calibrated LIGO data the glitch waveform estimated by the joint \bw{} inference. {We produce posterior distributions on the parameters of the injected signal before and after subtracting the glitch,} and we {show that removing the transient noise} effectively mitigates bias from broadband glitches. This study provides a baseline validation of existing techniques, while demonstrating waveform reconstruction improvements to the Bayesian algorithm for robust astrophysical characterization in glitch-prone detector data.
title Assessing and Mitigating the Impact of Glitches on Gravitational-Wave Parameter Estimation: a Model Agnostic Approach
topic General Relativity and Quantum Cosmology
Instrumentation and Methods for Astrophysics
url https://arxiv.org/abs/2311.09159