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Record W2042376058 · doi:10.1103/physrevb.67.085313

Magnetotransport in a two-dimensional electron gas in the presence of spin-orbit interaction

2003· article· en· W2042376058 on OpenAlexafffund
X. F. Wang, P. Vasilopoulos

Bibliographic record

VenuePhysical review. B, Condensed matter · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCondensed matter physicsMagnetoresistancePhysicsMagnetic fieldFermi gasElectrical resistivity and conductivityLandau quantizationSpin (aerodynamics)Spin–orbit interactionElectronElectron localization functionQuantum mechanics

Abstract

fetched live from OpenAlex

We evaluate the transport coefficients of a two-dimensional electron gas in the presence of a perpendicular magnetic field and of the spin-orbit interaction (SOI) described only by the Rashba term of strength \ensuremath{\alpha}. The SOI mixes the spin-up and spin-down states of neighboring Landau levels into two new, unequally spaced energy branches. The broadened density of states, as a function of the energy, and the longitudinal resistivity, as a function of the magnetic field, show beating patterns in agreement with observations. The positions of any two successive nodes in the beating pattern approximately determine the strength of the Rashba term. A strong SOI results in a splitting of the magnetoresistance peaks and a doubling of the number of the Hall plateaus. Each peak in the derivative of the Hall resistivity with respect to the magnetic field for \ensuremath{\alpha}=0 splits, for \ensuremath{\alpha}\ensuremath{\ne}0, into two peaks, whose separation \ensuremath{\Delta}B increases initially with \ensuremath{\alpha} and saturates for large \ensuremath{\alpha}.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.307
Teacher spread0.296 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations97
Published2003
Admission routes2
Has abstractyes

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