The recent discovery of gravitational waves and high-energy cosmic neutrinos, marked the beginning of a new era of the multimessenger astronomy. These new messengers, along with electromagnetic radiation and cosmic rays, give new insights into the most extreme energetic cosmic events. Among them supernovae explosion is one of the challenging targets of this new astronomical approach. Gravitational waves, much like neutrinos, are emitted from the innermost region of the core collapse supernova and thus convey information on the dynamics in the supernova core to the observer. They potentially carry information not only on the general degree of asymmetry in the dynamics of the core collapse supernova, but also more directly on the explosion mechanism, on the structural and compositional evolution of the protoneutron star, the rotation rate of the collapsed core, and the nuclear equation of state. The development of a new machine learning algorithm will be described to further improve the detectability of a gravitational wave signal from core collapse supernova and the results obtained will be discussed.

Multimessenger challenges for the detection of core collapse supernovae / DI PALMA, Irene; Cerdá-Durán, P.; Drago, Marco.; López, M.; Ricci, F.; Veutro, A.. - (2023), pp. 1-7. (Intervento presentato al convegno 38th International cosmic ray conference tenutosi a Nagoya, Giappone).

Multimessenger challenges for the detection of core collapse supernovae

Irene Di Palma
;
Marco. Drago
;
F. Ricci
;
A. Veutro
2023

Abstract

The recent discovery of gravitational waves and high-energy cosmic neutrinos, marked the beginning of a new era of the multimessenger astronomy. These new messengers, along with electromagnetic radiation and cosmic rays, give new insights into the most extreme energetic cosmic events. Among them supernovae explosion is one of the challenging targets of this new astronomical approach. Gravitational waves, much like neutrinos, are emitted from the innermost region of the core collapse supernova and thus convey information on the dynamics in the supernova core to the observer. They potentially carry information not only on the general degree of asymmetry in the dynamics of the core collapse supernova, but also more directly on the explosion mechanism, on the structural and compositional evolution of the protoneutron star, the rotation rate of the collapsed core, and the nuclear equation of state. The development of a new machine learning algorithm will be described to further improve the detectability of a gravitational wave signal from core collapse supernova and the results obtained will be discussed.
2023
38th International cosmic ray conference
multimessenger; machine learning; gravitational wave; core collapse supernovae
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Multimessenger challenges for the detection of core collapse supernovae / DI PALMA, Irene; Cerdá-Durán, P.; Drago, Marco.; López, M.; Ricci, F.; Veutro, A.. - (2023), pp. 1-7. (Intervento presentato al convegno 38th International cosmic ray conference tenutosi a Nagoya, Giappone).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1694047
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