MIT Probability Seminar

Monday, November 16, 2020 at 4:15pm to 5:15pm

Virtual Event

Featured Speaker :  Subhabrata Sen (Harvard University)

Title :  Large deviations for dense random graphs: beyond mean-field

Abstract : 

In a seminal paper, Chatterjee and Varadhan derived an LDP for the dense Erdős-Rényi random graph, viewed as a random graphon. This directly provides LDPs for continuous functionals such as subgraph counts, spectral norms, etc. In contrast, very little is understood about this problem if the underlying random graph is inhomogeneous or constrained

In this talk, we will explore large deviations for dense random graphs, beyond the ``mean-field" setting. In particular, we will study large deviations for uniform random graphs with given degrees, and a family of dense block model random graphs. We will establish the LDP in each case, and identify the rate function. In the block model setting, we will use this LDP to study the upper tail problem for homomorphism densities of regular sub-graphs. Our results establish that this problem exhibits a symmetry/symmetry-breaking transition, similar to one observed for Erdős-Rényi random graphs.

Based on joint works with Christian Borgs, Jennifer Chayes, Souvik Dhara, Julia Gaudio and Samantha Petti.

Event Type


Events By Interest


Events By Audience


Events By School

School of Science


prob_sem, aldixon


Department of Mathematics


Contact Email

Add to my calendar

Recent Activity

You're not going yet!

This event requires registration.