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Gwadaptive_scattering: an automated pipeline for scattered light noise characterization
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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.
Forward citations
Cited by 2 Pith papers
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Scattered-light noise coupling to strain readout is derived as full optomechanical transfer factors, recovering legacy models only in phase-dominated regimes and substantially revising Einstein Telescope low-frequency...
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New modeling of the stray light noise in the main arms of the Einstein Telescope
Stray light noise in Einstein Telescope arms is predicted to stay below the safety margin in ideal conditions, but beam offsets above 4 to 7 cm, tilts above 8 microradians, or strong point absorbers could breach it.
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