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Record W2803386305 · doi:10.1088/1361-648x/aad0b2

Spin–orbit effects on the spin and pseudospin polarization in ac-driven silicene

2018· article· en· W2803386305 on OpenAlexaff
Alexander López, Francisco Mireles, John Schliemann, Benjamín Santos

Bibliographic record

VenueJournal of Physics Condensed Matter · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTopological Materials and Phenomena
Canadian institutionsInstitut National de la Recherche Scientifique
FundersUniversidad Nacional Autónoma de MéxicoDeutsche Forschungsgemeinschaft
KeywordsSilicenePhysicsCondensed matter physicsQuasiparticleSpin (aerodynamics)Spin–orbit interactionPolarization (electrochemistry)Electric fieldSpin polarizationQuantum mechanicsSuperconductivityGraphene

Abstract

fetched live from OpenAlex

We study the pseudospin and spin dynamical effects in single-layer silicene due to a perpendicular electric field periodically driven and its interplay with the intrinsic and extrinsic (Rashba) spin-orbit interaction. We find that the spin nonconserving processes of the real spin of the quasiparticles in silicene, induced by the rather weak spin-orbit mechanisms, manifest themselves as shifts of the resonances of its quasienergy spectrum in the low coupling regime to the driving field. We show that there is an interesting cooperative effect among the, in principle, competing Rashba and intrinsic spin-orbit contributions. This is explicitly illustrated by exact and approximated analytical solutions of the dynamical equations. In addition, we show that a finite Rashba spin-orbit interaction is indeed necessary in order to achieve a nonvanishing spin polarization. As additional feature, trivial and nontrivial topological phases might be distinguished from each other as fast or slow dynamical fluctuations of the spin polarization. We mention the possible experimental detection schemes of our theoretical results and their relevance in new practical implementation of periodically driven interactions in silicene physics and related two-dimensional systems.

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 score0.417
Threshold uncertainty score0.711

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)0.0010.000

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 head0.246
Teacher spread0.236 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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