Pith. sign in

REVIEW 1 cited by

Translation-Invariant Gibbs States of Ising model: General Setting

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1710.07608 v1 pith:2WIRTIFB submitted 2017-10-20 math.PR math-phmath.MP

classification math.PRmath-phmath.MP
keywords graphinteractionsisingmathbbmodelstatesautomorphism-invariantgeneral
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
abstract

We prove that at any inverse temperature $\beta$ and on any transitive amenable graph, the automorphism-invariant Gibbs states of the ferromagnetic Ising model are convex combinations of the plus and minus states. This is obtained for a general class of interactions, that is automorphism-invariant and irreducible coupling constants. The proof uses the random current representation of the Ising model. The result is novel when the graph is not $\mathbb{Z}^d$, or when the graph is $\mathbb{Z}^d$ but endowed with infinite-range interactions, or even $\mathbb{Z}^2$ with finite-range interactions. Among the corollaries of this result, we can list continuity of the magnetization at any non-critical temperature, the differentiability of the free energy, and the uniqueness of FK-Ising infinite-volume measures.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Finitary codings for gradient models and a new graphical representation for the six-vertex model

    math.PR 2019-08 conditional novelty 8.0 of 10

    Gradient fields of low-temperature spin models (Ising, Potts, beach, six-vertex) are finitary factors of i.i.d. processes even when the models themselves are not.

Pith tools