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arXiv · 2107.07565

Gwadaptive_scattering: an automated pipeline for scattered light noise characterization

Stefano Bianchi·Alessandro Longo·Guillermo Valdes·Gabriela González·Wolfango Plastino
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Abstract

Scattered light noise affects the sensitivity of gravitational waves detectors. The characterization of such noise is needed to mitigate it. The time-varying filter empirical mode decomposition algorithm is suitable for identifying signals with time-dependent frequency such as scattered light noise (or scattering). We present a fully automated pipeline based on the pytvfemd library, a python implementation of the tvf-EMD algorithm, to identify objects inducing scattering in the gravitational-wave channel with their motion. The pipeline application to LIGO Livingston O3 data shows that most scattering noise is due to the penultimate mass at the end of the X-arm of the detector (EXPUM) and with a motion in the micro-seismic frequency range.

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Stefano Bianchi, Alessandro Longo, Guillermo Valdes, Gabriela González, Wolfango Plastino. 2021-07-15. Gwadaptive_scattering: an automated pipeline for scattered light noise characterization. https://doi.org/10.1088/1361-6382%2Fac88b0

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