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INPP Seminar | Nuclear matter in the FRIB & multi-messenger astronomy era, Sept. 20

The Institute of Nuclear and Particle Physics Seminar series presents Christian Drischler discussing "Nuclear matter in the FRIB & multi-messenger astronomy era" on Sept. 20 at 4 p.m.

Drischler is assistant professor of Physics & Astronomy at Ohio University.

In-person seminars will be in Lindley 321. For remote seminars, connection info for the video conference (TEAMS or ZOOM) and abstract of the talk will be communicated by email before the seminar. The emails are sent to the inpp-seminar mailing list. To be added to this mailing list, contact Prakash .

The host is Prakash.

Abstract : Born in the aftermath of core-collapse supernovae, neutron stars contain matter under extreme conditions of density and temperature. In recent years, neutron star observations have yielded novel insights into the nature of strongly interacting, neutron-rich matter in the high-density regime where current theoretical models are challenged. At the same time, chiral effective field theory (EFT) has developed into a powerful framework to study nuclear matter properties with quantified uncertainties in the moderate-density regime for modeling neutron stars. Furthermore, a few months ago, the new Facility for Rare Isotope Beams (FRIB) at Michigan State University opened its doors to scientific users, enabling experiments with nuclei in the very neutron-rich regime. In short, the next decade is expected to witness a strong interplay between neutron star observation, experiment, and theory, with stringent tests of nuclear predictions and great potential for discoveries.

In this INPP Seminar, I will discuss recent developments in EFT-based nuclear matter calculations and their implications for the structure of neutron stars. I will show how EFT, combined with new many-body ideas, enables the statistically robust uncertainty quantification of nuclear matter properties. Furthermore, I will motivate joint projects involving Bayesian machine learning and high-performance computing at the INPP.

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