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Record W2896104445 · doi:10.1109/essderc.2018.8486863

Si MOS technology for spin-based quantum computing

2018· preprint· en· W2896104445 on OpenAlexfundno aff
Louis Hutin, Benoît Bertrand, R. Maurand, Alessandro Crippa, Matias Urdampilleta, Y.J. Kim, A. Amisse, Heorhii Bohuslavskyi, L. Bourdet, Sylvain Barraud, X. Jeh, Yann‐Michel Niquet, M. Sanquer, Christopher Bäuerle, Tristan Meunier, S. De Franceschi, M. Vinet

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsnot available
FundersHorizon 2020 Framework ProgrammeIndigenous and Northern Affairs CanadaCentre National de la Recherche ScientifiqueAgence Nationale de la Recherche
KeywordsQubitRealization (probability)Quantum dotQuantum computerNanowireFabricationSpin (aerodynamics)NanotechnologyOptoelectronicsQuantumPhysicsElectronicsQuantum gateMaterials scienceComputer scienceElectrical engineeringQuantum mechanicsEngineering

Abstract

fetched live from OpenAlex

We present recent advances made towards the realization of hole and electron spin quantum bits (qubits) localized within Si Quantum Dots (QDs). These devices, operated at cryogenic temperatures, can be defined by slightly modifying an SOI NanoWire FET fabrication flow, and are thus particularly relevant in the perspective of large-scale co-integration of qubits and their cryogenic control electronics.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.014
GPT teacher head0.271
Teacher spread0.257 · 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 designTheoretical or conceptual
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

Citations17
Published2018
Admission routes1
Has abstractyes

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