Speaker
Elena Cuoco
(EGO & SNS)
Description
The application of Machine and Deep learning techniques in astrophysics has gained significant attention also within the field of Gravitational Wave (GW) science, where numerous teams in the LIGO-Virgo collaboration have been exploring the potential of machine learning algorithms. These algorithms have been tested using both simulated and real data from LIGO and Virgo interferometers, focusing on tasks such as noise reduction and characterizing astrophysical signals.
I will provide specific examples demonstrating the effectiveness of Machine Learning in identifying and classifying transient signals arising from noise disturbances or GW events, including Core Collapse Supernovae and Compact Binary Coalescence events.
Primary author
Elena Cuoco
(EGO & SNS)
