Convolutional Neural Networks for signal detection in real LIGO data

Searching the data of gravitational-wave detectors for signals from compact binary mergers is a computationally demanding task. Recently, machine learning algorithms have been proposed to address current and future challenges. However, the results of these publications often differ greatly due to differing choices in the evaluation procedure. The Machine Learning Gravitational-Wave Search Challenge was organized to resolve these issues and produce a unified framework for machine-learning search evaluation. Six teams submitted contributions, four of which are based on machine learning …

algorithms astro-ph.im binary challenges convolutional neural networks cs.lg current data detection evaluation future gr-qc ligo machine machine learning machine learning algorithms mergers networks neural networks publications searching signal