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Record W2593471898 · doi:10.1038/srep43553

Manipulation of a Nuclear Spin by a Magnetic Domain Wall in a Quantum Hall Ferromagnet

2017· article· en· W2593471898 on OpenAlexaff
Marek Korkusiński, Paweł Hawrylak, Hongwu Liu, Y. Hirayama

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsUniversity of OttawaNational Research Council Canada
Fundersnot available
KeywordsCondensed matter physicsFerromagnetismSpin (aerodynamics)PhysicsDomain (mathematical analysis)Magnetic domainQuantum mechanicsMagnetic fieldMagnetizationMathematics

Abstract

fetched live from OpenAlex

The manipulation of a nuclear spin by an electron spin requires the energy to flip the electron spin to be vanishingly small. This can be realized in a many electron system with degenerate ground states of opposite spin polarization in different Landau levels. We present here a microscopic theory of a domain wall between spin unpolarized and spin polarized quantum Hall ferromagnet states at filling factor two with the Zeeman energy comparable to the cyclotron energy. We determine the energies and many-body wave functions of the electronic quantum Hall droplet with up to N = 80 electrons as a function of the total spin, angular momentum, cyclotron and Zeeman energies from the spin singlet ν = 2 phase, through an intermediate polarization state exhibiting a domain wall to the fully spin-polarized phase involving the lowest and the second Landau levels. We demonstrate that the energy needed to flip one electron spin in a domain wall becomes comparable to the energy needed to flip the nuclear spin. The orthogonality of orbital electronic states is overcome by the many-electron character of the domain - the movement of the domain wall relative to the position of the nuclear spin enables the manipulation of the nuclear spin by electrical means.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.234
Teacher spread0.224 · 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 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

Citations3
Published2017
Admission routes1
Has abstractyes

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