Speaker
Zewei Xiong
(GSI Helmholtzzentrum für Schwerionenforschung)
Description
The rapid neutron-capture process ($r$-process), known to operate in neutron-star merger (NSM) remnants, produces heavy elements whose radioactive decay deposits energy into the ejecta and powers a distinctive thermal glow called kilonova. However, an online implementation of the $r$-process in simulations is challenging due to the associated large number of isotopes in a full nuclear network. In this talk, we will present a machine learning method to emulate the $r$-process and its energy generation that can be efficiently incorporated in hydrodynamic simulations. We use this method to study the effects of $r$-process heating on the properties of NSM ejecta and kilonova.
Primary authors
Zewei Xiong
(GSI Helmholtzzentrum für Schwerionenforschung)
Dr
Oliver Just
(GSI Helmholtzzentrum für Schwerionenforschung)
Prof.
Gabriel Martínez-Pinedo
(GSI Helmholtzzentrum für Schwerionenforschung)
