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Record W2117032256 · doi:10.1002/rsa.10020

Very rapid mixing of the Glauber dynamics for proper colorings on bounded‐degree graphs

2001· article· en· W2117032256 on OpenAlexaff
Martin Dyer, Catherine Greenhill, Mike Molloy

Bibliographic record

VenueRandom Structures and Algorithms · 2001
Typearticle
Languageen
FieldMathematics
TopicMarkov Chains and Monte Carlo Methods
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGlauberMathematicsCombinatoricsDegree (music)Mixing (physics)Constant (computer programming)GraphBounded functionDiscrete mathematicsPhysicsComputer scienceMathematical analysisQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract Recent results have shown that the Glauber dynamics for graph colorings has optimal mixing time when (i) the graph is triangle‐free and Δ‐regular and the number of colors k is a small constant fraction smaller than 2Δ, or (ii) the graph has maximum degree Δ and k =2Δ. We extend both these results to prove that the Glauber dynamics has optimal mixing time when the graph has maximum degree Δ and the number of colors is a small constant fraction smaller than 2Δ. © 2002 John Wiley & Sons, Inc. Random Struct. Alg., 20, 98–114, 2002

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.051
GPT teacher head0.308
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations19
Published2001
Admission routes1
Has abstractyes

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