Classification of noise sources in LIGO gravitational wave observations using deep neural networks and model explainability analysis

Abstract

This document uses state of the art image classification techniques to automate the detection of noise sources in gravitational wave observations from the Laser Interferometer Gravitational-Wave Observatory (LIGO). Additionally, it analyzes the resulting model using post-hoc local interpretation methodologies with the intent of defining possible paths of improvement.