Speaker
Description
Nuclear matter equation of state (EOS) is essential for understanding the properties of supernovae explosions and neutron stars. We explore the application of In-medium Similarity Renormalization Group (IMSRG) method in nuclear matter calculations. A many-body framework is built to construct EOSs for nuclear matter with a range of proton factions using IMSRG from different nuclear interaction inputs. To enable efficient exploration of the input parameter space and facilitate statistical uncertainty quantification, we construct a fast and accurate emulator for the IMSRG framework based on a machine learning technique called parametric matrix model (PMM). PMM emulator captures the complex dependence of the EOS on low-energy constants and allows for systematic propagation of nuclear interaction uncertainties to the EOS and neutron star observables.
