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Record W2538495405 · doi:10.1109/essderc.2016.7599655

A manufacturable process for single electron charge detection, a step towards quantum computing

2016· preprint· en· W2538495405 on OpenAlexafffund
Gabriel Droulers, Serge Ecoffey, Dominique Drouin, Michel Pioro-Ladrière

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldComputer Science
TopicQuantum-Dot Cellular Automata
Canadian institutionsCanadian Institute for Advanced ResearchInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsInterfacingQuantum cellular automatonFabricationTransistorPlanarComputer scienceQuantum computerCoulomb blockadeProcess (computing)QuantumCharge (physics)Characterization (materials science)OptoelectronicsCellular automatonMaterials scienceElectronic engineeringNanotechnologyElectrical engineeringPhysicsVoltageEngineeringComputer hardwareQuantum mechanics

Abstract

fetched live from OpenAlex

This paper presents the fabrication, electrical characterization, and simulation of planar single electron transistors. Two single electron transistors facing each other have been used to demonstrate single charge detection. The manufacturable fabrication process combined with both single charge detection and the simulation tool are a powerful platform for quantum cellular automata that can be applied for interfacing classical computing with future quantum computing.

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: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.029
GPT teacher head0.282
Teacher spread0.252 · 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
Published2016
Admission routes2
Has abstractyes

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