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Record W2321946263 · doi:10.1103/physrevb.88.115417

Zeeman coupling and screening corrections to skyrmion excitations in graphene

2013· article· en· W2321946263 on OpenAlexaff
Wenchen Luo, R. Côté

Bibliographic record

VenuePhysical Review B · 2013
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsSkyrmionZeeman effectPhysicsZeeman energyExcitationCondensed matter physicsLandau quantizationSpin (aerodynamics)Coupling (piping)Quantum mechanicsElectronMagnetic fieldMaterials science

Abstract

fetched live from OpenAlex

At half-filling of the fourfold degenerate Landau levels $|n|\ensuremath{\ge}1$ in graphene, the ground states are spin-polarized quantum Hall states that support spin skyrmion excitations for $|n|=1,2,3$. Working in the Hartree-Fock approximation, we compute the excitation energy of an unbound spin skyrmion-antiskyrmion excitation as a function of the Zeeman coupling strength for these Landau levels. We find for both the bare and screened Coulomb interactions that the spin skyrmion-antiskyrmion excitation energy is lower than the excitation energy of an unbound spin-$1/2$ electron-hole pair in a finite range of Zeeman coupling in Landau levels $|n|=1,2,3$. This range decreases rapidly for increasing Landau level index and is extremely small for $|n|=3.$ For valley skyrmions, which should be present at $1/4$ and $3/4$ fillings of the Landau levels $|n|=1,2,3$, we show that screening corrections are more important in the latter case. It follows that an unbound valley skyrmion-antiskyrmion excitation has lower energy at $3/4$ filling than at $1/4.$ We compare our results with recent experiments on spin and valley skyrmion excitations in graphene.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.845
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.029
GPT teacher head0.350
Teacher spread0.321 · 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 designBench or experimental
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

Citations18
Published2013
Admission routes1
Has abstractyes

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