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Record W4406735471 · doi:10.48550/arxiv.2501.11396

Band representations in Strongly Correlated Settings: The Kitaev Honeycomb Model

2025· preprint· en· W4406735471 on OpenAlexfundno aff
Axel Fünfhaus, Mikel García‐Díez, Maia G. Vergniory, Thilo Kopp, Stephen M. Winter, Roser Valentí

Bibliographic record

VenueArXiv.org · 2025
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAdvanced Condensed Matter Physics
Canadian institutionsnot available
FundersMinisterio de Ciencia e InnovaciónCanada Excellence Research Chairs, Government of CanadaDeutsche ForschungsgemeinschaftEuropean Commission
KeywordsHoneycombStatistical physicsTheoretical physicsPhysicsCondensed matter physicsMathematicsGeometry

Abstract

fetched live from OpenAlex

In the study of quantum spin liquids, the Kitaev model plays a pivotal role due to the fact that its ground state is exactly known as well as the fact that it may be realized in strongly frustrated materials such as $α$-RuCl${}_3$. While topological insulators and superconductors can be investigated by means of topological band theory -- in particular the topological quantum chemistry (TQC) formalism -- the Kitaev model evades such a treatment, as it is not possible to set up a proper single-particle Green's function for it. We instead associate spin operators with ``orbitals'' that give rise to a band structure. It is thereby possible to analyze the corresponding excitation spectrum engendered by these localized excitations by means of TQC. Special attention is given to the low-energy topological edge mode spectrum. Our work sheds light on the question how the TQC formalism may be generalized to strongly correlated and topologically ordered systems like the Kitaev 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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.024
GPT teacher head0.293
Teacher spread0.269 · 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 designSimulation or modeling
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
Published2025
Admission routes1
Has abstractyes

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