International team of scientists from Scuola Normale Superiore, Tor Vergata University, Swinburne University and the Nicolaus Copernicus Astronomical Center of the Polish Academy of Sciences (CAMK PAN), represented by PhD student Filip Morawski, proposed a new method of searching for gravitational waves emitted by Core-Collapse supernova explosions CCSN.

Publications on this topic appeared in “Machine Learning Science and Technology”. The international scientific team is investigating the latest CCSN models generated on the basis of hydrodynamic simulations of the collapse process of the neutrino-driven star core.

The gravitational waves obtained in this way were then added to the “simulated non-stationary noise of the Virgo detectors and the Einstein Telescope (planned gravitational wave detector)”. The novelty of the proposed CCSN signal search method is the use of a “convolution neural network (CNN) in combination with an algorithm that searches for signals in cosmic noise called the Wavelet Detection Filter (WDF)”.