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Record W2617434493 · doi:10.1103/physrevb.96.115132

Fluctuation-induced continuous transition and quantum criticality in Dirac semimetals

2017· article· en· W2617434493 on OpenAlexafffund
Laura Classen, Igor F. Herbut, Michael M. Scherer

Bibliographic record

VenuePhysical review. B./Physical review. B · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTopological Materials and Phenomena
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaDeutsche ForschungsgemeinschaftU.S. Department of Energy
KeywordsDirac fermionPhysicsQuantum phase transitionRenormalization groupQuantum critical pointFermionPhase transitionMassless particleQuantum mechanicsCritical exponentScalingQuantumMathematical physicsCondensed matter physicsMathematics

Abstract

fetched live from OpenAlex

Thermal phase transitions are successfully described by fluctuations of an appropriate order parameter, which further allows classification of the transition into first or second order. However, some quantum analogs of thermal phase transitions defy this description and identifying the mechanisms behind these unconventional processes will fundamentally improve our understanding of matter. Here, the authors provide a thorough study of such a transition, which has been experimentally accessed in graphene: the emergence of a Kekul\'e valence bond solid. Additional gapless quantum fluctuations of Dirac electrons change the nature of this transition from first to second order. Using a nonperturbative functional renormalization group approach, the authors advance the state-of-the-art estimates for the corresponding critical exponents and predict measurable corrections to scaling.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.028
GPT teacher head0.387
Teacher spread0.360 · 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 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

Citations60
Published2017
Admission routes2
Has abstractyes

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