MétaCan
Menu
Back to cohort

Coherent control of two individual electron spins and influence of hyperfine coupling in a double quantum dot

2011· article· en· W2004943981 on OpenAlexaff
Seigo Tarucha, Takayuki Obata, Michel Pioro-Ladrière, Roland Brunner, T. Kubo, Y. Tokura

Bibliographic record

VenueJournal of Physics Conference Series · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsUniversité de Sherbrooke
FundersJapan Society for the Promotion of Science
KeywordsHyperfine structureCondensed matter physicsSpinsPhysicsResonance (particle physics)ElectronSpin (aerodynamics)Atomic physicsDipoleSpin polarizationElectron paramagnetic resonanceElectric fieldCoupling (piping)Spin echoNuclear magnetic resonanceMaterials scienceMagnetic resonance imagingNuclear physicsQuantum mechanics

Abstract

fetched live from OpenAlex

Electric dipole spin resonance of two individual electrons and the influence of hyperfine coupling on the spin resonance are studied for a double quantum dot equipped with a micro-magnet. The spin resonance occurs by oscillating the electron in each dot at microwave (MW) frequencies in the presence of a micro-magnet induced stray field. The observed continuous wave (CW) and time-resolved spin resonances are consistent with calculations in which the MW induced AC electric field and micro-magnet induced stray field are taken into account. The influence of hyperfine coupling causes an increase and broadening of the respective CW spin resonance peaks through dynamical nuclear polarization when sweeping up the magnetic field. This behaviour appears stronger for the larger of the two spin resonance peaks and in general becomes more pronounced as the MW power increases, both reflecting that the electron-nuclei interaction is more efficient for the stronger spin resonance. In addition the hyperfine coupling effect only becomes pronounced when the MW induced AC magnetic field exceeds the fluctuating nuclear field.

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 score0.587
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.024
GPT teacher head0.246
Teacher spread0.222 · 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
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Physics Conference SeriesSame topicQuantum and electron transport phenomenaFrench-language works237,207