Pith. sign in

REVIEW 1 cited by

Using memory to identify phase transitions on a Cayley Tree

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 1304.7008 v2 pith:3MYA66B2 submitted 2013-04-25 cond-mat.stat-mech gr-qc

classification cond-mat.stat-mechgr-qc
keywords memoryphasetransitioncarlocayleyclearmontesignal
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

We provide a concrete and systematic connection between the statistical physics of the Ising ferromagnet on a Cayley tree, and the study of memory in exponentially expanding spaces. Memory turns out to be a clear signal of the `Bethe-Peierls' phase transition, and the average of memory divided by its standard deviation provides a clear signal of the `spin-glass' transition temperature. Numerical Monte Carlo simulations are used to make transparent the existence of the two different transition temperatures. The quantities used to spot the phase transitions with Monte Carlo could be useful when studying other systems where analytical methods don't work.

Discussion (0). Sign in 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. Stable valleys in the glassy landscape of a low-density parity-check (LDPC) code

    cond-mat.stat-mech 2026-07 conditional novelty 6.0 of 10

    For the Tanner-Hamming [7,4,3] LDPC model on a high-girth random regular graph, low-energy valleys separate canonical and microcanonical instability, yielding ensemble inequivalence in a non-random, unfrustrated spin glass.

Pith tools