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Two-matrix models and biorthogonal polynomials

2015· reference-entry· en· W2887688077 on OpenAlexaff
Marco Bertola

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldChemistry
TopicMolecular spectroscopy and chirality
Canadian institutionsConcordia University
Fundersnot available
KeywordsBiorthogonal systemHermitian matrixMatrix (chemical analysis)Pure mathematicsMathematicsCauchy distributionAlgebra over a fieldMathematical analysisComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This article considers two cases of two-matrix models that are amenable to biorthogonal polynomials: Itzykson-Zuber interaction and Cauchy interaction. The features and applications of the biorthogonal polynomials relevant to either case are discussed, but first the article provides an overview of chain-matrix models. It then describes the Itzykson-Zuber Hermitian two-matrix model and the Christoffel–Darboux identities, along with the spectral curve. It also examines the so-called mixed correlation functions that are involved in the combinatorial applications of the two-matrix model before concluding with an analysis of the Cauchy two-matrix model, which in a ‘complication scale’ turns out to lie in between the one-matrix model and the Itzykson-Zuber two-matrix model.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.036
GPT teacher head0.318
Teacher spread0.281 · 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 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

Citations3
Published2015
Admission routes1
Has abstractyes

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