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Record W1849849131 · doi:10.48550/arxiv.1507.03027

Critical points of Potts and O($N$) models from eigenvalue identities in periodic Temperley-Lieb algebras

2015· preprint· en· W1849849131 on OpenAlexfundno aff
Jesper Lykke Jacobsen

Bibliographic record

VenuearXiv (Cornell University) · 2015
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsnot available
FundersInstitut Universitaire de FranceUniversity of MelbourneAgence Nationale de la RechercheYork University
KeywordsPotts modelEigenvalues and eigenvectorsTransfer matrixMathematicsCombinatoricsLattice (music)ExponentConformal mapMathematical physicsPure mathematicsPhysicsMathematical analysisIsing modelQuantum mechanics

Abstract

fetched live from OpenAlex

In previous work with Scullard, we defined a graph polynomial P_B(q,T) that gives access to the critical temperature T_c of the q-state Potts model on a general two-dimensional lattice L. It depends on a basis B, containing n x m unit cells of L, and the relevant root of P_B(q,T) was observed to converge quickly to T_c in the limit n,m to infinity. Moreover, in exactly solvable cases there is no finite-size dependence at all. We reformulate this method as an eigenvalue problem within the periodic Temperley-Lieb algebra. This corresponds to taking m to infinity first, so the bases B are semi-infinite cylinders of circumference n. The limit implies faster convergence in n, while maintaining the n-independence in exactly solvable cases. In this setup, T_c(n) is determined by equating the largest eigenvalues of two topologically distinct sectors of the transfer matrix. Crucially, these two sectors determine the same critical exponent in the continuum limit, and the observed fast convergence is thus corroborated by results of conformal field theory. We obtain similar results for the dense and dilute phases of the O(N) loop model, using now a transfer matrix within the dilute periodic Temperley-Lieb algebra. The eigenvalue formulation allows us to double the size n for which T_c(n) can be obtained, using the same computational effort. We study in details three significant cases: (i) bond percolation on the kagome lattice, up to n = 14; (ii) site percolation on the square lattice, to n = 21; and (iii) self-avoiding polygons on the square lattice, to n = 19. Convergence properties of T_c(n) and extrapolation schemes are studied in details for the first two cases. This leads to rather accurate values for the percolation thresholds: p_c = 0.524404999167439(4) for bond percolation on the kagome lattice, and p_c = 0.59274605079210(2) for site percolation on the square lattice.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.198
Teacher spread0.150 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2015
Admission routes1
Has abstractyes

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