Neural network deciphers gravitational waves from merging neutron stars in a second

Binary neutron star mergers emit gravitational waves followed by light. To fully exploit these observations and avoid missing key signals, speed is crucial. An interdisciplinary team of researchers presents a novel machine learning method that can analyze gravitational waves emitted by 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.
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