Probing nuclear physics with supernova gravitational waves and machine learning
Mitra A. Orel D. Abylkairov Y.S. Shukirgaliyev B. Abdikamalov E.
1 April 2024Oxford University Press
Monthly Notices of the Royal Astronomical Society
2024#529Issue 43582 - 3592 pp.
Core-collapse supernovae (CCSNe) are sources of powerful gravitational waves (GWs). We assess the possibility of extracting information about the equation of state (EOS) of high density matter from the GW signal. We use the bounce and early post-bounce signals of rapidly rotating supernovae. A large set of GW signals is generated using general relativistic hydrodynamics simulations for various EOS models. The uncertainty in the electron capture rate is parametrized by generating signals for six different models. To classify EOSs based on the GW data, we train a convolutional neural network (CNN) model. Even with the uncertainty in the electron capture rates, we find that the CNN models can classify the EOSs with an average accuracy of about 87 per cent for a set of four distinct EOS models.
gravitational waves , methods: data analysis , transients: supernovae
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Center for Astrophysical Surveys, National Center for Supercomputing Applications, University of Illinois Urbana-Champaign, Urbana, 61801, IL, United States
Department of Physics, Nazarbayev University, 53 Kabanbay Batyr ave, Astana, 010000, Kazakhstan
Department of Astronomy, University of Illinois Urbana-Champaign, Urbana, 61801, IL, United States
School of Materials Science and Green Technologies, Kazakh-British Technical University, 59 Tole Bi Street, Almaty, 050000, Kazakhstan
Department of Computer Science, Nazarbayev University, 53 Kabanbay Batyr ave, Astana, 010000, Kazakhstan
Energetic Cosmos Laboratory, Nazarbayev University, 53 Kabanbay Batyr ave, Astana, 010000, Kazakhstan
Heriot-Watt International Faculty, Zhubanov University, 263 Zhubanov brothers str, Aktobe, 030000, Kazakhstan
Fesenkov Astrophysical Institute, 23 Observatory str, Almaty, 050020, Kazakhstan
Department of Computation and Data Science, Astana It University, 55/11 Mangilik El ave, Astana, 010000, Kazakhstan
Center for Astrophysical Surveys
Department of Physics
Department of Astronomy
School of Materials Science and Green Technologies
Department of Computer Science
Energetic Cosmos Laboratory
Heriot-Watt International Faculty
Fesenkov Astrophysical Institute
Department of Computation and Data Science
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