Microscopic Modeling of Hot and Dense Neutron-Rich Matter

Texas A&M University, College Station TX

Investigators

Abstract

At the end of their lives, massive stars undergo highly energetic supernova explosions, which enrich the interstellar medium with heavy elements that then go on to become the building blocks for new stars, planets, and even life. Although the basic physical processes that drive supernova explosions are generally understood, a detailed description of the explosion dynamics and the properties of the matter created under the extreme conditions of density and temperature remain elusive. These properties are crucial for a precise understanding of elemental production in supernovae and the chemical evolution of our galaxy. To probe more deeply into the physics of supernova explosions, neutrinos play a pivotal role. Neutrinos are abundantly produced during supernovae, and since they interact weakly with the surrounding matter, they can carry information about the deep microphysical environments in which they are produced. Understanding neutrino physics in supernovae therefore remains a key challenge in both astrophysics and nuclear physics. This project investigates the role of nuclear many-body correlations and mean fields in modifying neutrino absorption and scattering rates in supernova environments, starting from microscopic models of nuclear two-body and three-body forces. The work develops new statistical inference tools for propagating uncertainties in the nuclear force to observable properties of the neutrinos created in supernovae. A significant outcome of the project will be a set of consistent equations of state and neutrino opacities for homogeneous nuclear matter across a range of densities, temperatures, and proton fractions that are important for astrophysical simulations. These will be tabulated in a form that is usable by the astrophysics simulation community in order to make more reliable predictions for the neutrino signals from galactic core-collapse supernovae that may be observed through ground-based neutrino detectors. The microscopic calculations carried out in this project are computationally intensive but made tractable through the use of new generative machine learning models also developed during the course of the project. This project advances the objectives of "Windows on the Universe: the Era of Multi-Messenger Astrophysics", one of the 10 Big Ideas for Future NSF Investments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.