The pressure, densities and first order phase transitions associated with multidimensional SOFT
Shmuel Friedland, Uri N. Peled

TL;DR
This paper investigates the mathematical properties of the pressure function in multidimensional Potts models, establishing its convexity and Lipschitz continuity, and linking phase transitions to points of non-differentiability, with computational methods applied to specific models.
Contribution
The paper provides rigorous proofs of pressure properties and develops computable bounds, applying them to confirm and extend previous heuristic results for the monomer-dimer model.
Findings
Pressure is Lipschitz and convex.
First order phase transitions occur at non-differentiable points of pressure.
Numerical methods accurately compute pressure and density entropy.
Abstract
We study theoretical and computational properties of the pressure function for subshifts of finite type on the integer lattice , multidimensional SOFT, which are called Potts models in mathematical physics. We show that the pressure is Lipschitz and convex. We use the properties of convex functions to show rigorously that the phase transition of the first order correspond exactly to the points where the pressure is not differentiable. We give computable upper and lower bounds for the pressure, which can be arbitrary close the values of the pressure given a sufficient computational power. We apply our numerical methods to confirm Baxter's heuristic computations for two dimensional monomer-dimer model, and to compute the pressure and the density entropy as functions of two variables for the two dimensional monomer-dimer model.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMathematical Dynamics and Fractals · Markov Chains and Monte Carlo Methods · Theoretical and Computational Physics
