• 9 September 2026
  • 3:30 EDT
 Nuclear Science Seminar Titled: Pathways to the Nuclear Matter Equation of State: Simulations, AI/ML, and Novel Analyses Uncovering the dense nuclear matter equation of state (EOS) is at the heart of numerous theoretical, experimental, and observational campaigns worldwide. Prominent efforts include studies aiming to understand the apparent peak in the speed of sound at high density and to constrain the isospin dependence of the EOS. Relativistic heavy-ion collisions provide unique opportunities to probe hot and dense nuclear matter and extract information about its EOS. Doing so, however, requires both reliable dynamical modeling and observables with strong sensitivity to the underlying nuclear interaction. I will discuss several recent directions toward these goals, including developments in microscopic transport simulations, data analysis, and the use of machine learning to maximize inference.