Neural network deciphers gravitational waves from merging neutron stars in a second – March 05, 2025

Artist’s impression of two merging neutron stars and the gravitational waves they produce. © MPI-IS / A. Posada
Machine learning method could revolutionize multi-messenger astronomy
Observing binary neutron star mergers is high on the wish list of astronomers. These collisions of exotic, compact stellar remnants emit gravitational waves followed by light, providing unique opportunities to study gravity and matter under extreme conditions. Speed is critical to fully exploit these observations and avoid missing key signals. In a study published today in Nature, an interdisciplinary team of researchers presents a novel machine learning method to analyze gravitational waves emitted from neutron star collisions almost instantaneously – even before the merger is fully observed. A neural network processes the data and enables a fast search for visible light and other electromagnetic signals emitted during the collisions. This new method could be instrumental in preparing the field for the next generation of observatories.