Speaker
Dr
Irene Di Palma
(INFN)
Description
Core collapse supernovae, among the most energetic explosions in the
modern Universe, have not been detected yet, while
gravitational waves have been detected from mergers of binary black
holes and binary neutron stars.
To enhance the detection efficiency of such category of signals we
present a nonlinear method based on convolutional
neural network algorithm to extract core collapse supernova signals
embedded in Gaussian noise with spectral behaviour
of Advanced LIGO and Virgo detectors.
Using this new approach we can classify signal from noise and identify
the signal more efficiently than the algorithm
currently used by the LIGO-Virgo Collaboration to search for
gravitational wave transient signals.
Collaboration name
Virgo
Primary author
Dr
Irene Di Palma
(INFN)
