Solving Random Matrix Models with Positivity - Henry Lin

Explore the intricacies of random matrix models in this high-energy theory seminar presented by Henry Lin from Princeton University. Delve into the fundamentals of matrix models, their importance, and the concept of matrix integrals. Examine the complexities of two-matrix models and loop equations. Investigate the search space and positivity constraints, including the Hamburg moment problem and single finite constraints. Analyze multicut solutions and the relaxed positivity constraint, with a focus on single matrix explanation. Discover potential future directions in the field, including double cut and Isin model applications. Gain valuable insights into solving random matrix models using positivity techniques in this comprehensive lecture from the Institute for Advanced Study.

Introduction
What is a matrix model
Why Matrix Integrals
Two Matrix Model
Loop Equations
Search Space
Positivity constraints
Hamburg moment problem
Single finite constraints
Multicut solutions
Relaxed positivity constraint
Single matrix explanation
Future directions
Double cut
Isin model