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Record W2156627911 · doi:10.1142/s0217979204026949

PINNING AND SLIDING OF QUANTUM HALL STRIPES AND BUBBLES

2004· article· en· W2156627911 on OpenAlexaff
R. Côté, Mei-Rong Li, Herbert Fertig, Alexandre Faribault, Hangmo Yi

Bibliographic record

VenueInternational Journal of Modern Physics B · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsUniversité de Sherbrooke
FundersNational Science Foundation
KeywordsCondensed matter physicsPhysicsSemiclassical physicsSymmetry breakingQuantum Hall effectFilling factorKubo formulaSaddle pointQuantum mechanicsQuantumConductivityElectron

Abstract

fetched live from OpenAlex

We report on the calculation of the frequency-dependent conductivity of the quantum Hall stripes and bubble crystals that form in high Landau level. We use the replica and Gaussian variational methods (GVM) with a dynamical matrix obtained from the time-dependent Hartree-Fock approximation. In the stripe state, we go beyond the semiclassical approximation of the saddle point equations obtained with the GVM and demonstrate the existence of a quantum depinning transition as a function of filling factor. Below a critical filling factor, the pinned state is described by a replica symmetry breaking (RSB) solution that gives resonant peaks in the frequency-dependent conductivity in both directions, parallel and perpendicular to the stripes orientation. These peaks shift to zero frequency as the critical filling is approached. Above the critical filling, we find a depinned stripe state described by a partial replica symmetry breaking solution in which there is free sliding only along the stripe direction. The transition has a Kosterlitz-Thouless character and includes a jump in the low-frequency exponent of the dynamical conductivity. In the bubble crystals a semiclassical approximation yields a pinning peak frequency and resonance width that generally decrease with increasing filling factor, in accordance with recent microwave absorption experiments.

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 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 score0.184
Threshold uncertainty score0.340

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 science0.0000.000
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 head0.012
GPT teacher head0.245
Teacher spread0.233 · 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

Citations1
Published2004
Admission routes1
Has abstractyes

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