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Record W4210403204 · doi:10.21468/scipost.report.3566

Report on 2009.11880v4

2021· peer-review· en· W4210403204 on OpenAlexafffund
Han Ma, Sung-Sik Lee

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldMathematics
TopicAlgebraic structures and combinatorial models
Canadian institutionsMcMaster UniversityPerimeter Institute
FundersInstitut Périmètre de physique théoriqueNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaMinistry of Colleges and UniversitiesInnovation, Science and Economic Development Canada
KeywordsComputer scienceGeography

Abstract

fetched live from OpenAlex

The β-functions describe how couplings run under the renormalization group flow in field theories.In general, all couplings that respect the symmetry and locality are generated under the renormalization group flow, and the exact renormalization group flow is characterized by the β-functions defined in the infinite dimensional space of couplings.In this paper, we show that the renormalization group flow is highly constrained so that the β-functions defined in a measure zero subspace of couplings completely determine the β-functions in the entire space of couplings.We provide a quantum renormalization group-based algorithm for reconstructing the full β-functions from the β-functions defined in the subspace.As examples, we derive the full β-functions for the O(N ) vector model and the O L (N ) × O R (N ) matrix model entirely from the β-functions defined in the subspace of single-trace couplings.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.883
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.8830.867

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 head0.065
GPT teacher head0.359
Teacher spread0.293 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2021
Admission routes2
Has abstractyes

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Same topicAlgebraic structures and combinatorial modelsFrench-language works237,207