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Record W2322841532 · doi:10.1103/physrevb.90.241303

Ultrafast high-fidelity initialization of a quantum-dot spin qubit without magnetic fields

2014· article· en· W2322841532 on OpenAlexfundno aff
Jonathan D. Mar, Jeremy J. Baumberg, Xiulai Xu, A. C. Irvine, D. A. Williams

Bibliographic record

VenuePhysical Review B · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilNatural Sciences and Engineering Research Council of CanadaCambridge Commonwealth TrustUniversity of GlasgowHigher Education Funding Council for England
KeywordsPhysicsQuantum dotInitializationQubitQuantum tunnellingSpin (aerodynamics)Excited stateCondensed matter physicsMagnetic fieldSpinsAtomic physicsQuantum mechanicsQuantumComputer science

Abstract

fetched live from OpenAlex

We demonstrate the initialization of a single quantum-dot hole spin with high fidelity (lower bound $>97%$), on picosecond time scales, and without the need for magnetic fields. Using the initialization scheme based on rapid electric-field ionization of a resonantly excited exciton, this is achieved by employing a self-assembled quantum dot with a low conduction-to-valence band offset ratio, allowing control of the relative electron and hole tunneling rates over three orders of magnitude. This large difference in tunneling rates could permit spin-storage efficiencies $>99.5%$ by fast-switching to a low electric-field condition. Our results may provide a practical route towards ultrafast high-fidelity initialization of individual quantum-dot hole spins for the implementation of quantum error correction in a scalable spin-based quantum computer.

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)0.001
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
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.011
GPT teacher head0.278
Teacher spread0.267 · 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

Citations18
Published2014
Admission routes1
Has abstractyes

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