A characterization method for low-frequency environmental noise in LIGO

TL;DR

This paper introduces a linear regression-based method to identify and quantify low-frequency environmental noise sources in LIGO, aiding noise mitigation without additional experimental setup.

Contribution

The proposed approach uses LASSO regression to analyze detector and sensor data, providing a practical, resource-efficient way to characterize low-frequency noise in gravitational-wave observatories.

Findings

Successfully identified coupling of ground motion below 10 Hz with detector noise

Validated the method with two real-world examples

Can be implemented using existing LIGO resources

Abstract

We present a method to characterize the noise in ground-based gravitational-wave observatories such as the Laser Gravitational-Wave Observatory (LIGO). This method uses linear regression algorithms such as the least absolute shrinkage and selection operator (LASSO) to identify noise sources and analyzes the detector output versus noise witness sensors to quantify the coupling of such noise. Our method can be implemented with currently available resources at LIGO, which avoids extra coding or direct experimentation at the LIGO sites. We present two examples to validate and estimate the coupling of elevated ground motion at frequencies below 10 Hz with noise in the detector output.