Time: Starting on Nov 3, Tuesdays, 4:40pm CET
Online via Zoom (link)
Limited physical attendance if regulations allow:
Seminar Room 3
Max Planck Institute for the Physics of Complex Systems
Noethnitzer Str. 38
Summary: Suppose someone gave you a terabyte of data on an epidemic. What are the theoretical concepts you need to know in order to understand collective behaviour in such a system? Technological breakthroughs in biology and the social sciences now give unprecedented access to microscopic states of non-equilibrium systems, requiring a rethinking about our approaches to understanding collective degrees of freedom in complex systems. In this lecture, we will take an interdisciplinary perspective on the concepts necessary to identify and understand collective order in space and time. We will begin by introducing core concepts from non-equilibrium statistical physics, such as stochastic processes, field theory, renormalisation group theory and non-equilibrium phase transitions, and complement these tools with approaches from data science and machine learning that allow identifying collective degrees of freedom in high-dimensional measurements. We will synthesise these lessons using examples from current research.
Required prior knowledge: Statistical physics
Password for PDF files is the last name of the lecturer.