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The intersection of statistical mechanics and mathematical analysis has proved a fertile ground for mathematical physics and probability, and in the decades since lattice gases were first proposed as a model for describing physical systems at the atomic level, our understanding of them has grown tremendously. A book that provides a comprehensive account of the methods used in the study of phase transitions for Ising models and classical and quantum Heisenberg models has been long overdue. This book, written by one of the masters of the subject, is just that.
Topics covered include correlation inequalities, Lee–Yang theorems, the Peierls method, the Hohenberg–Mermin–Wagner method, infrared bounds, random cluster methods, random current methods, and BKT transition. The final section outlines major open problems to inspire future work.
This is a must-have reference for researchers in mathematical physics and probability and serves as an entry point, albeit advanced, for students entering this active area.
Our main goal is to prove the result of Deift and Trogdon (2018) on universality for the Toda eigenvalue algorithm to compute the top eigenvalue of a random real symmetric or Hermitian matrix H chosen from some random matrix ensemble. We concentrate first on the real symmetric case: The modifications that are necessary in the Hermitian case are given in Section 3.10.