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Record W4410846733 · doi:10.1134/s008154382501002x

Modularity of Landau–Ginzburg Models

2025· article· en· W4410846733 on OpenAlexaff
Charles F. Doran, Andrew Harder, Ludmil Katzarkov, Михаил Александрович Овчаренко, Victor Przyjalkowski

Bibliographic record

VenueProceedings of the Steklov Institute of Mathematics · 2025
Typearticle
Languageen
FieldMathematics
TopicAlgebraic structures and combinatorial models
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsModularity (biology)Cognitive scienceComputer sciencePsychologyBiologyEvolutionary biology

Abstract

fetched live from OpenAlex

For each smooth Fano threefold, we construct a family of Landau–Ginzburg models which satisfy many expectations coming from different aspects of mirror symmetry. These Landau–Ginzburg models are log Calabi–Yau varieties with proper superpotential maps; they admit open algebraic torus charts on which the superpotential function $$\mathsf{w}$$ restricts to a Laurent polynomial satisfying a deformation of the Minkowski ansatz; and the general fibres of $$\mathsf{w}$$ are Dolgachev–Nikulin dual to the anticanonical hypersurfaces in the initial Fano threefold. To construct the family of models, we develop the deformation theory of Landau–Ginzburg models in arbitrary dimension, following the work of Katzarkov, Kontsevich, and Pantev (2017), with special emphasis on the case of Landau–Ginzburg models obtained from Laurent polynomials. Our proof of the Dolgachev–Nikulin mirror symmetry is by detailed case-by-case analysis, which refines Cheltsov and Przyjalkowski’s work (published in the same volume of the journal) on the verification of the Katzarkov–Kontsevich–Pantev conjecture.

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)0.000
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 score0.053
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.029
GPT teacher head0.275
Teacher spread0.246 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

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