Deep learning algorithms for gravitational waves core-collapse supernova detection

Author(s):  
M. Lopez ◽  
M. Drago ◽  
I. Di Palma ◽  
F. Ricci ◽  
P. Cerda-Duran
2021 ◽  
Vol 103 (6) ◽  
Author(s):  
M. López ◽  
I. Di Palma ◽  
M. Drago ◽  
P. Cerdá-Durán ◽  
F. Ricci

2020 ◽  
Vol 1 (2) ◽  
pp. 025014 ◽  
Author(s):  
Alberto Iess ◽  
Elena Cuoco ◽  
Filip Morawski ◽  
Jade Powell

2015 ◽  
Vol 811 (2) ◽  
pp. 86 ◽  
Author(s):  
Takaaki Yokozawa ◽  
Mitsuhiro Asano ◽  
Tsubasa Kayano ◽  
Yudai Suwa ◽  
Nobuyuki Kanda ◽  
...  

2012 ◽  
Vol 86 (4) ◽  
Author(s):  
J. Logue ◽  
C. D. Ott ◽  
I. S. Heng ◽  
P. Kalmus ◽  
J. H. C. Scargill

2016 ◽  
Vol 12 (S329) ◽  
pp. 428-428
Author(s):  
Ko Nakamura ◽  
Shunsaku Horiuchi ◽  
Masaomi Tanaka ◽  
Kazuhiro Hayama ◽  
Tomoya Takiwaki ◽  
...  

AbstractThe next Galactic supernova is expected to bring great opportunities for the direct detection of gravitational waves, full flavor neutrinos, and multi-wavelength photons. To prepare for appropriate observations of these multi-messenger signals, we use a long-term numerical simulation of the core-collapse supernova and discuss detectability of the signals in different situations. By exploring the sequential multi-messenger signals of a nearby CCSN, we discuss preparations for maximizing successful studies of such an unprecedented stirring event.


2019 ◽  
Vol 486 (2) ◽  
pp. 2238-2253 ◽  
Author(s):  
H Andresen ◽  
E Müller ◽  
H-Th Janka ◽  
A Summa ◽  
K Gill ◽  
...  

2021 ◽  
Vol 104 (10) ◽  
Author(s):  
Marek J. Szczepańczyk ◽  
Javier M. Antelis ◽  
Michael Benjamin ◽  
Marco Cavaglià ◽  
Dorota Gondek-Rosińska ◽  
...  

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