Machine Learning for Fundamental Physics

Apr 13, 2022 - 11:00 am to 12:00 pm

SLAC, Kavli 3rd Floor Conf. Room

Ben Nachman (LBNL) In Person and Zoom


I will describe a research program aimed at advancing the potential for discovery and interdisciplinary collaboration by approaching Particle Physics and Astrophysics (PPA) challenges through the lens of modern machine learning (ML). This research program has two complementary components. Ab initio simulations are a powerful tool of PPA science 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.