Widely Applied Mathematics Seminar

Date: 

Thursday, November 4, 2021, 3:00pm to 4:00pm

Location: 

Zoom

"Statistical Physics Analysis of Species-Rich Ecosystems" with Giulio Biroli, Professor of Theoretical Physics, ENS Paris.

"Statistical Physics Analysis of Species-Rich Ecosystems" with Giulio Biroli, Professor of Theoretical Physics, ENS Paris.

Dr. Biroli is professor of theoretical physics at École Normale Supérieure, Paris, since 2018. He is the PI of the Simons collaboration « Cracking the glass problem » and holds a PRAIRIE chair on interdisciplinary applications of Machine Learning. He is the director of the Beg Rohu summer school of statistical physics and condensed matter. Dr. Biroli has published more than 130 peer-reviewed articles. His research focuses on statistical physics, theoretical condensed matter, theoretical physics, interdisciplinary applications of physics to machine learning, and biology. He is the Editor-in-Chief of the Journal of Statistical Physics

Abstract: I will first start with a general introduction to theoretical ecology, stressing the reasons that make connections with statistical physics interesting and timely. I will then focus on Lotka-Volterra equations, which provide a general model to study large assemblies of strongly interacting degrees of freedom in many different fields: biology, economy, and in particular ecology. I will present our ongoing works on Lotka-Volterra equations for species-rich ecosystems. I will show that such systems display different “phases” and collective behaviors, from simple regimes with a single equilibrium to complex ones characterized by either an exponential number of multiple equilibria, all poised at the edge of stability, or chaotic dynamics. I will show how statistical physics methods allow to shed new light on open and debated questions in ecology and to provide new theoretical perspectives. Finally, I will present a study of the interplay between artificial selection at the community level and ecological dynamics. 

Visit the event page for more information. Register in advance. 

Contact: cbaek@seas.harvard.edu