A data mining approach to signal processing in Laser Interferometer Gravitational-Wave Observatory (LIGO) Fscan data
The Laser Interferometer Gravitational-Wave Observatory (LIGO) detectors are designed to capture and record gravitational wave strain signals from astrophysical sources. The Fscan family of algorithms is a key signal processing tool for analyzing the spectral content of LIGO data. An area of ongoing investigation are features of the LIGO Hanford strain data in the sub-100Hz range that are not fully understood. This work utilizes a statistically-oriented, data-mining approach to analyze three related but distinct subjects in LIGO Hanford data from the O3-era observing run: the coherence of auxiliary data channels with the strain, the potential for coherence between the Hanford and Livingston interferometers not caused by astrophysical sources, and the shifting density of high-power spectral lines in strain data.
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