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Record W2039123633 · doi:10.1143/jpsj.77.031011

Magnetic and Electrical Control of Electron-Nuclear Spin Coupling in GaAs Double Quantum Dots

2008· article· en· W2039123633 on OpenAlexaff
Seigo Tarucha, Jonathan Baugh

Bibliographic record

VenueJournal of the Physical Society of Japan · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsUniversity of Waterloo
FundersJapan Society for the Promotion of Science
KeywordsZeeman effectPhysicsQuantum dotZeeman energyMagnetic fieldCondensed matter physicsHyperfine structureElectronCoulomb blockadePauli exclusion principleTriplet stateAtomic physicsVoltageQuantum mechanics

Abstract

fetched live from OpenAlex

We magnetically and electrically control spin coupling between electrons and nuclei in a vertical GaAs double quantum dot in the Pauli spin blockade regime to characterize the two-electron exchange energy and the dynamic nuclear polarization (DNP). The Pauli blockade is lifted by a hyperfine-mediated transition from an electron triplet state to the singlet state. This transition progressively occurs when the triplet-singlet separation or exchange energy J is compensated by tuning either Zeeman energy with external magnetic field (i.e., magnetic control) or inter-dot energy detuning with bias voltage (i.e., electrical control). The blockade is then lifted with a current step for sweeping up an external magnetic field. The J value, which is evaluated from the step position for various inter-dot detuning values, is consistent with calculation. DNP takes place through the hyperfine coupling near the current step, leading to a shifted current step to lower external magnetic field for the down-sweep. For the electrical control, a similar current step appears for sweeping bias voltage. In this case we are able to control the two-electron state energies in a relevant manner based on real time before DNP is significantly influenced, because the voltage sweep is much faster than the magnetic field sweep. We use this technique to distinguish the current step with and without DNP contributions, and therefore quantify the nuclear Overhauser fields with external magnetic field as a parameter. We present a simple phenomenological model to reproduce the experiment and also discuss a possible approach to realize the full DNP.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score0.410

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 head0.008
GPT teacher head0.224
Teacher spread0.216 · 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 designObservational
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

Citations6
Published2008
Admission routes1
Has abstractyes

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