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Record W2471452602 · doi:10.1103/physrevb.94.161101

Tilt-induced phase transitions in even-denominator fractional quantum Hall states at the ZnO interface

2016· article· en· W2471452602 on OpenAlexafffund
Wenchen Luo, Tapash Chakraborty

Bibliographic record

VenuePhysical review. B./Physical review. B · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsUniversity of Manitoba
FundersCanada Research Chairs
KeywordsLandau quantizationCondensed matter physicsQuantum Hall effectQuantum phase transitionFractional quantum Hall effectFilling factorPhysicsFermi gasMagnetic fieldCoulombPhase transitionElectronQuantum oscillationsPhase (matter)Composite fermionQuantum spin Hall effectCompressibilityQuantum mechanics

Abstract

fetched live from OpenAlex

Strongly interacting electrons in a ZnO quantum well reveal intriguing electronic properties that were not observed in traditional semiconductor systems, such as in a GaAs heterojunction. In a tilted magnetic field, the even-denominator fractional quantum Hall states in this system exhibit unique phase transitions that necessitate a proper understanding. Since here the Landau level gap is very small, it is essential to consider a screened Coulomb potential in order to include the effects of all Landau levels. We observe an incompressible state--compressible state phase transition induced by the tilted field with different properties for the $\frac{3}{2}$ and $\frac{7}{2}$ filling factors. Additionally, the disappearance of the $\frac{5}{2}$ state in the experiment is most likely due to the presence of a screened Coulomb potential. We, however, propose that a wider quantum well may help to stabilize the incompressible phase of the $\frac{5}{2}$ filling factor, and thereby make the fractional quantum Hall effect observable in this state.

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), 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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.016
GPT teacher head0.362
Teacher spread0.346 · 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

Citations10
Published2016
Admission routes2
Has abstractyes

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