Analyzing Standing Accretion Shock Instability Using Gravitational Waves
Faculty Mentor Name
Michele Zanolin
Format Preference
Poster
Abstract
The detection of gravitational waves (GW) from Core Collapse Supernovae (CCSNe) would build a new understanding of the internal physics of a Core collapse Supernova (CCSN). One of the features of these GW is called standing accretion shock instability (SASI). In order to detect and reconstruct the SASI component of a CCSN GW, our team will be upgrading the current software. More explicitly by implementing MuLaSECc (Multi-Layer Signal Enhancement with Coherent Wave Burst and CNN [Convolutional Neural Network]) we can artificially decrease the role of the noise recorded by LIGO. By advancing this program further we can increase the potential of multi-messenger astrophysics since CCSNe can be studied with GW, electromagnetic waves, and neutrinos at the same time.
Analyzing Standing Accretion Shock Instability Using Gravitational Waves
The detection of gravitational waves (GW) from Core Collapse Supernovae (CCSNe) would build a new understanding of the internal physics of a Core collapse Supernova (CCSN). One of the features of these GW is called standing accretion shock instability (SASI). In order to detect and reconstruct the SASI component of a CCSN GW, our team will be upgrading the current software. More explicitly by implementing MuLaSECc (Multi-Layer Signal Enhancement with Coherent Wave Burst and CNN [Convolutional Neural Network]) we can artificially decrease the role of the noise recorded by LIGO. By advancing this program further we can increase the potential of multi-messenger astrophysics since CCSNe can be studied with GW, electromagnetic waves, and neutrinos at the same time.