Free Entropy Theory and Random Matrices

February 24 - 28, 2025


Free probability was introduced by Voiculescu in the 80’s in an attempt to study the notorious free group factors, which are certain fundamental—and in many ways prototypical—examples of von Neumann algebras. The subject has been intimately connected with random matrix theory ever since Voiculescu’s breakthrough result that the large N-limits of independent random matrices are freely independent. The notion of free entropy, which quantifies this connection, has recently seen spectacular success in applications to von Neumann algebras, including the resolution of the long-standing Peterson–Thom conjecture through the use of Hayes’s 1-bounded entropy.

Free probability has transformed into an interdisciplinary field connecting operator algebras, harmonic analysis, probability, and combinatorics. This workshop will bring together experts and early career researchers from operator algebras and random matrix theory to better understand this intersection and expand the reach of free entropy methods. Topics will include:

  • Free entropy dimension and 1-bounded entropy
  • Strong and weak convergence of laws in random matrix theory
  • Applications to von Neumann algebras, random graphs, and other topics
  • Consequences of the resolution of the Peterson–Thom Conjecture


This workshop will include a poster session.  A request for posters will be sent to registered participants before the workshop.

FET2025 Program Flyer


Organizing Committee

Rolando de Santiago (California State University, Long Beach (CSU Long Beach))
Ben Hayes (University of Virginia)
Srivatsav Kunnawalkam Elayavalli (University of California, San Diego (UCSD))
Brent Nelson (Michigan State University)
Nikhil Srivastava (University of California, Berkeley (UC Berkeley))