Physics Club: Benjamin Nachman, Lawrence Berekley National Laboratory, “Machine Learning for Fundamental Physics”

I will describe an exciting and rapidly growing research program aimed at advancing the potential for discovery and interdisciplinary collaboration by approaching Particle, Nuclear, and Astro Physics challenges through the lens of modern machine learning (ML). This research program has two complementary components. Ab initio simulations are a powerful tool of fundamental physics and the first component described in the talk will be the optimal combination of simulations with ML. The second component will focus on simulation-free problems where ML can be used to identify patterns in high-dimensional feature spaces that would be unfindable with traditional methods.
Host: Ian Moult (ian.moult@yale.edu)