A Sensitive Test of Non-Gaussianity in Gravitational-wave Detector Data

Abstract

Methods for parameter estimation of gravitational-wave data assume that detector noise is stationary and Gaussian. Real data deviates from these assumptions, which causes bias in the inferred parameters and incorrect estimates of the errors. We develop a sensitive test of non-Gaussianity for real gravitational-wave data which measures meaningful parameters that can be used to characterize these effects. As a test case, we investigate the quality of data cleaning performed by the LIGO-Virgo-KAGRA collaboration around GW200129, a binary black hole signal which overlapped with the noise produced by the radio frequency modulation. We demonstrate that a significant portion of the non-Gaussian noise is removed below 50 Hz, yet some of the noise still remains after the cleaning; at frequencies above 85 Hz, there is no excess noise removed. We also show that this method can quantify the amount of non-Gaussian noise in continuous data, which is useful for general detector noise investigations. To do that, we estimate the difference in non-Gaussian noise in the presence and absence of light scattering noise.

6 pages, 3 figures. PRD accepted

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• Evidence for eccentricity in the population of binary black holes observed by LIGO-Virgo-KAGRA
• Evidence for a correlation between binary black hole mass ratio and black-hole spins
• Revisiting the evidence for precession in GW200129 with machine learning noise mitigation
• Which black hole is spinning? Probing the origin of black-hole spin with gravitational waves
• The anti-aligned spin of GW191109: glitch mitigation and its implications
• Do both black holes spin in merging binaries? Evidence from GWTC-4 and astrophysical implications
• Neural Post-Einsteinian Test of General Relativity with the Third Gravitational-Wave Transient Catalog