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Record W4394709595 · doi:10.48550/arxiv.2404.06333

On the 576-fold periodicity of the spectrum SQFT: The proof of the lower bound via the Anderson duality pairing

2024· preprint· en· W4394709595 on OpenAlexfundno aff
Theo Johnson-Freyd, Mayuko Yamashita

Bibliographic record

VenuearXiv (Cornell University) · 2024
Typepreprint
Languageen
FieldMathematics
TopicSpectral Theory in Mathematical Physics
Canadian institutionsnot available
FundersCore Research for Evolutional Science and TechnologyJapan Society for the Promotion of ScienceMinistry of Colleges and UniversitiesInstitut Périmètre de physique théoriqueNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsPairingDuality (order theory)Fold (higher-order function)Spectrum (functional analysis)MathematicsUpper and lower boundsPure mathematicsCombinatoricsMathematical physicsPhysicsComputer scienceQuantum mechanicsMathematical analysisSuperconductivity

Abstract

fetched live from OpenAlex

We are aimed at giving a differential geometric, and accordingly physical, explanation of the 576-periodicity of TMF. In this paper, we settle the problem of giving the lower bound 576. We formulate the problem as follows: we assume a spectrum $\mathrm{SQFT}$ with some conditions, suggest from physical considerations about the classifying spectrum for two-dimensional $\mathcal{N}=(0,1)$-supersymmetric quantum field theories, and show that the periodicity of $\mathrm{SQFT}$ is no less than 576. The main tool for the proof is the analogue of the Anderson duality pairing introduced by the second-named author and Tachikawa. We do not rely on the Segal-Stolz-Teichner conjecture, so in particular we do not use any comparison map with TMF.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.022
Threshold uncertainty score0.932

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0030.003
Research integrity0.0000.002
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 head0.098
GPT teacher head0.228
Teacher spread0.130 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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