Automating noise sources identification in gravitational wave detectors

First measured in 2015, gravitational waves (GWs) — ripples in the fabric of spacetime caused by massive, dense accelerating objects — require extremely sensitive instrumentation to be detected. Excess microseismic noise at the location of the detector, caused by things as innocuous as sea waves, can cause so-called scattered light glitches. Such noise can affect GW detectors, like Virgo and the Laser Interferometer Gravitational-Wave Observatory (LIGO), and reduce their sensitivity.

GW detectors, kilometers in size, are made of several optical components. Hence, identifying scattering culprits can be difficult and time-consuming. Longo et al. automated the process of culprit identification and monitoring using a method called adaptive data decomposition.

“Adaptive decomposition is fast and precise, which is relevant for glitch subtraction in next-generation detectors. These foresee an increased rate of detections, which can overlap with glitches,” said author Alessandro Longo. “This is known to negatively impact parameter estimation of the astrophysical source.”

The technique provides mathematical functions highly correlated with scattering predictors computed from the position data of the detector’s optical components. This allows researchers to quickly locate the culprit — the most correlated object — and monitor it.

“Glitch subtraction is relevant for precise sky localization of the [GW] source, which is in turn relevant for the detection of an electromagnetic counterpart, as optical telescopes need a precise localization of the gravitational wave source in the sky,” said Longo.

The researchers are currently applying adaptive decomposition for the purpose of glitch subtraction, with promising results. Longo says they are looking forward to implementing it as a standard, fully automated tool for noise subtraction in both Virgo and other current and upcoming GW detectors.

Source: “Identification and monitoring of scattered light noise sources in laser interferometers with adaptive algorithms,” Alessandro Longo, Stefano Bianchi, Guillermo Valdes, Nicolas Arnaud, Francesco Di Renzo, Matteo Montani, and Wolfango Plastino, Journal of Applied Physics (2025). The article can be accessed at https://doi.org/10.1063/5.0273058 .