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Record W4312077425 · doi:10.1103/physrevb.106.235135

Superconductivity in the twisted bilayer transition metal dichalcogenide <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mrow><mml:mi>WSe</mml:mi></mml:mrow><mml:mn>2</mml:mn></mml:msub></mml:math>: A quantum cluster study

2022· article· lv· W4312077425 on OpenAlexafffund
Mathieu Bélanger, Jérôme Fournier, David Sénéchal

Bibliographic record

VenuePhysical review. B./Physical review. B · 2022
Typearticle
Languagelv
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsInstitut quantiqueUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSuperconductivityBilayer grapheneTwistCondensed matter physicsCluster (spacecraft)PhysicsHubbard modelField (mathematics)Materials scienceQuantum mechanicsGrapheneGeometryComputer scienceMathematics

Abstract

fetched live from OpenAlex

The observation of flat energy bands in transition metal dichalcogenide bilayers such as twisted ${\mathrm{WSe}}_{2}$ makes those materials interesting prospects for reproducing the behavior observed in graphene-based systems. We use an effective Hubbard model providing a description of twisted ${\mathrm{WSe}}_{2}$ to explore the presence of superconductivity, which was previously reported in experiments. Using both the variational cluster approximation and cluster dynamical mean-field theory, we predict the existence of chiral superconductivity of type $d\ifmmode\pm\else\textpm\fi{}id$ that can be tuned by the twist angle and by the application of a perpendicular displacement field in both electron- and hole-doped systems.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0460.003

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 head0.032
GPT teacher head0.306
Teacher spread0.274 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations27
Published2022
Admission routes2
Has abstractyes

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