Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash 75 tok/s
Gemini 2.5 Pro 49 tok/s Pro
GPT-5 Medium 34 tok/s
GPT-5 High 32 tok/s Pro
GPT-4o 101 tok/s
GPT OSS 120B 471 tok/s Pro
Kimi K2 200 tok/s Pro
2000 character limit reached

Lectures on the Ising and Potts models on the hypercubic lattice (1707.00520v1)

Published 3 Jul 2017 in math.PR, math-ph, and math.MP

Abstract: Phase transitions are a central theme of statistical mechanics, and of probability more generally. Lattice spin models represent a general paradigm for phase transitions in finite dimensions, describing ferromagnets and even some fluids (lattice gases). It has been understood since the 1980s that random geometric representations, such as the random walk and random current representations, are powerful tools to understand spin models. In addition to techniques intrinsic to spin models, such representations provide access to rich ideas from percolation theory. In recent years, for two-dimensional spin models, these ideas have been further combined with ideas from discrete complex analysis. Spectacular results obtained through these connections include the proofs that interfaces of the two-dimensional Ising model have conformally invariant scaling limits given by SLE curves, that the connective constant of the self-avoiding walk on the hexagonal lattice is given by $\sqrt{2+\sqrt 2}$. In higher dimensions, the understanding also progresses with the proof that the phase transition of Potts models is sharp, and that the magnetization of the three-dimensional Ising model vanishes at the critical point.

Citations (87)
List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Ai Generate Text Spark Streamline Icon: https://streamlinehq.com

Paper Prompts

Sign up for free to create and run paper prompts using GPT-5.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.

Authors (1)

Youtube Logo Streamline Icon: https://streamlinehq.com