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Record W4412969078 · doi:10.1117/12.3067689

Opto-electronic T centre quantum processors

2025· article· en· W4412969078 on OpenAlexaff
Daniel Higginbottom

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsComputer scienceQuantumPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

Silicon colour centres are an emerging quantum information platform with technological appeal: they emit in or near the optical telecommunications bands, host long coherence spin qubits, and integrate with silicon photonic and electronic circuits for scalable on-chip fabrication. In particular, the silicon T centre has been identified as a candidate for distributed quantum computing. Cavity-integrated T centres show dramatic Purcell enhancements, enabling faster and more coherent emission. Indistinguishable emission from separate T centre devices has enabled entanglement between T centre processors in separate cryostats. In this talk, I present the most recent T centre entanglement results and introduce a new class of opto-electronic T centre devices combining optical resonators and PIN junctions. These devices enable a host of new spin-photon techniques including electrically-injected single-photon emission, electrical spin initialization, and electrically-triggered remote entanglement schemes. These techniques expand the toolbox of controls available for T centre processors and can be readily extended to other silicon colour centres including the popular G and W centres.

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 score0.006
Threshold uncertainty score0.019

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 science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.003
GPT teacher head0.220
Teacher spread0.217 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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