Andrea Liu – Machine Learning Glassy Dynamics
Amphi Jaurès (29 Rue d'Ulm)Thursday 10th of November 2022, Andrea Liu (University of Pennsylvania) Title: Machine Learning Glassy Dynamics Abstract: The three-dimensional glass transition is an infamous example of an emergent collective phenomenon in many-body systems that is stubbornly resistant to microscopic understanding using traditional statistical physics approaches. Establishing the connection between microscopic properties and the glass transition requires reducing vast quantities of microscopic information to a few relevant microscopic variables and their distributions. I will demonstrate how machine learning, designed for dimensional reduction, can provide a natural way forward when standard statistical physics tools fail. We have […]