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Record W4395090861 · doi:10.1117/12.3012606

Scalable fault tolerance: quantum technologies with silicon colour centres

2024· article· en· W4395090861 on OpenAlexaff
Stephanie Simmons

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicQuantum Computing Algorithms and Architecture
Canadian institutionsPhoton Etc (Canada)
Fundersnot available
KeywordsScalabilityFault toleranceComputer scienceQuantumQuantum computerSiliconDistributed computingOptoelectronicsMaterials scienceDatabasePhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

The future global quantum internet will require high-performance matter-photon interfaces at scale. The highly demanding technological requirements indicate that the matter-photon interfaces currently under study all have potentially unworkable drawbacks, and there is a global race underway to identify the best possible new alternative. For overwhelming commercial and quantum reasons, silicon is the best possible host for such an interface. Silicon is not only the most developed integrated photonics and electronics platform by far, isotopically purified silicon-28 has also set records for quantum lifetimes at both cryogenic and room temperatures [1]. Despite this, the vast majority of research into photon-spin interfaces has notably focused on visible-wavelength colour centres in other materials. In this talk I will introduce a variety of silicon colour centres and discuss their properties in isotopically purified silicon-28. Some of these centres have zero-phonon optical transitions in the telecommunications bands [2], some have long-lived spins in their ground states [3], and some, including the newly rediscovered T centre, have both [4] and can be integrated into silicon photonics chips at scale [5]. <br/> <br/> [1] K. Saeedi, S. Simmons, J.Z. Salvail, et al. Science 342:830 (2013). <br/> [2] C. Chartrand, L. Bergeron, K.J. Morse, et al. Phys. Rev. B 98:195201 (2018). <br/> [3] K. Morse, R. Abraham, A. DeAbreu, et al. Science Advances 3:e1700930 (2017). <br/> [4] L. Bergeron, C. Chartrand, A.T.K. Kurkjian, et al. PRXQuantum 1:020301 (2020). <br/> [5] D. Higginbottom, A.T.K. Kurkjian, C. Chartrand et al. Nature 607:266 (2022).

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.007
GPT teacher head0.223
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 designSimulation or modeling
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

Citations1
Published2024
Admission routes1
Has abstractyes

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