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Record W4412870988 · doi:10.1117/12.3063171

Design parameters of the silicon nanocavities for single photon sources emitting in telecom wavelength

2025· article· en· W4412870988 on OpenAlexaff
Rezoana Bente Arif, Arez Nosratpour, Zahra Khatami

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsWavelengthOptoelectronicsSiliconPhotonTelecommunicationsNanophotonicsMaterials scienceOpticsPhysicsComputer science

Abstract

fetched live from OpenAlex

The scalability of quantum photonic circuits is challenged by the need for single-photon generation, with silicon emerging as the most scalable material for integrating new and existing photonic systems. Bullseye cavities, also known as circular Bragg gratings, have recently received attention for single-photon generation and transmission due to their exceptional capacity to intensify and focus emission from single photon sources over long distances with precise wavelength selection. Achieving high quantum efficiency of one of the carbon-related color centers (G centers) in silicon-based circular Bragg gratings has not been explored yet. This study investigates critical parameters affecting photon transmission, including the Purcell factor, maximum electric field, and photon collection efficiency at a wavelength of 1279 nm (G centers). Our study shows that changes in the ring number and numerical aperture affected the Purcell factor, photon collection efficiency, and the maximum electric field. In addition, the Purcell factor enhancement was observed by adding a gold layer at the bottom of the substrate.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

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 communication0.0000.000
Open science0.0010.000
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 head0.017
GPT teacher head0.216
Teacher spread0.199 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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