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Record W2607552475 · doi:10.1103/physrevb.96.035309

Quantum lifetime in ultrahigh quality GaAs quantum wells: Relationship to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi mathvariant="normal">Δ</mml:mi><mml:mrow><mml:mn>5</mml:mn><mml:mo>/</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:math> and impact of density fluctuations

2017· article· lv· W2607552475 on OpenAlexafffund
Qi Qian, James Nakamura, Saeed Fallahi, Geoffrey C. Gardner, John Watson, S. Lüscher, Joshua Folk, G. A. Csáthy, Michael J. Manfra

Bibliographic record

VenuePhysical review. B./Physical review. B · 2017
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsUniversity of British Columbia
FundersBasic Energy SciencesNatural Sciences and Engineering Research Council of CanadaU.S. Department of Energy
KeywordsLandau quantizationExcitationPhysicsQuantum wellCondensed matter physicsQuality (philosophy)Quantum Hall effectShubnikov–de Haas effectQuantumQuantum mechanicsMagnetic fieldQuantum oscillationsElectronFermi gas

Abstract

fetched live from OpenAlex

We consider the quantum lifetime derived from low-field Shubnikov--de Haas oscillations as a metric of the quality of the two-dimensional electron gas in GaAs quantum wells that expresses large excitation gaps of the $\ensuremath{\nu}=\frac{5}{2}$ fractional quantum Hall state in the $N=1$ Landau level. In high quality samples, small density inhomogeneities dramatically impact the amplitude of Shubnikov--de Haas oscillations such that the canonical method [cf. Coleridge, Phys. Rev. B 44, 3793 (1991)] for determination of the quantum lifetime substantially underestimates ${\ensuremath{\tau}}_{\text{q}}$ unless density inhomogeneity is explicitly considered. We have developed a method that can be used to determine density inhomogeneity and extract the intrinsic ${\ensuremath{\tau}}_{\text{q}}$ by analyzing the Shubnikov--de Haas oscillations. However, even after accounting for inhomogeneity, ${\ensuremath{\tau}}_{\text{q}}$ does not correlate well with sample quality as measured by ${\mathrm{\ensuremath{\Delta}}}_{5/2}$, the excitation gap of the fractional quantum Hall state at 5/2 filling.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.897
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0290.003

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 head0.023
GPT teacher head0.302
Teacher spread0.279 · 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 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

Citations32
Published2017
Admission routes2
Has abstractyes

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