Présidents de session
Combined analysis of nuclear and astrophysics information, Bayesian approach, and machine learning
- Arnaud Le Fèvre (GSI Helmholtzzentrum für Schwerionenforschung GmbH)
Combined analysis of nuclear and astrophysics information, Bayesian approach, and machine learning
- David Tsang (University of Bath)
With recent advances in neutron star observations, major progress has been made in determining the pressure of neutron star matter at high density. This pressure is constrained by the neutron star deformability, determined from gravitational waves emitted in a neutron-star merger, and measurements of radii of two neutron stars, using a new X-ray observatory on the International Space Station....
The data-driven Bayesian model averaging is a rigorous statistical approach to combining multiple models for a unified prediction. Compared with the individual model, it provides more reliable information, especially for problems involving apparent model dependence. In this work, within both the non-relativistic Skyrme energy density functional and the nonlinear relativistic mean field model,...
Astrophysical observations of neutron stars allow us to study the physics of matter at extreme conditions which are beyond the scope of any terrestrial experiments. In this work, we perform a Bayesian analysis putting together the available knowledge from the nuclear physics experiments, observations of different X-ray sources, and gravitational wave events to constrain the equation of state...
The Equation of State (EoS) is crucial for understanding the structure of compact objects such as neutron stars. In the conservative hypothesis of a purely nucleonic composition of neutron star matter, the EoS is fully determined in terms of the so-called nuclear matter parameters (NMPs), which, in principle, can be determined from nuclear theory and experiments, though with error bars....
Through continuous progress in nuclear theory and experiment and an increasing number of neutron-star observations, a multitude of information about the equation of state (EOS) for matter at extreme densities is available. Here, we apply these different pieces of data individually to a broad set of physics-agnostic candidate EOSs and analyze the resulting constraints. Specifically, we make use...
Inferences of the nuclear symmetry energy from heavy-ion collisions are currently based on the comparison of measured observables and transport model simulations. Only the expectation values of observables over all considered events are used in these approaches, however, observables can be obtained event-by-event both in experiments and transport model simulations. By using the light gradient...
We studied alpha-decay half-lives of 84 <= Z <= 92 in the semiclassical WKB approximation frame work using the density-dependent cluster model and the density distribution described by various Korea-IBS-Daegu-SKKU (KIDS) models. Main goal of this work is to find a correlation between alpha-decay half-lives and the stiffness of the symmtery energy. Parameters of KIDS model are determined to...
Recovering the nuclear matter parameters (NMPs), crucial elements in neutron star equations of state for the nucleonic core configuration, is a significant ongoing task in nuclear astrophysics. This involves utilizing various experimental data and astrophysical observations through a Bayesian approach. However, the conventional method of computing the equation of state (EoS) and solving the...
