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Record W3008601337 · doi:10.1109/jstqe.2020.2975588

Enhanced Small-Signal Responsivity in Silicon Microring Photodetector Based on Two-Photon Absorption

2020· article· en· W3008601337 on OpenAlexafffund
Yang Ren, Vien Van

Bibliographic record

VenueIEEE Journal of Selected Topics in Quantum Electronics · 2020
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsResponsivityPhotodetectorOptoelectronicsOpticsSiliconResonatorMaterials scienceDetectorSIGNAL (programming language)DemodulationHeterodyne detectionPhysicsTelecommunicationsComputer scienceLaser

Abstract

fetched live from OpenAlex

We experimentally investigated methods of enhancing the small-signal responsivity of a silicon pin microring photodetector based on two-photon absorption for detecting small optical signals in the telecommunication wavelength range. Two approaches are demonstrated, the first exploiting the bistability effect in the nonlinear microring resonator while the second employing an optical bias at a different wavelength to increase the differential responsivity. We achieved a small-signal responsivity of 180 mA/W with the first approach and 141 mA/W with the second approach, both of which represent almost 10-fold enhancement over direct detection of small optical signals by the same silicon pin microring detector. Our techniques have potential applications in amplitude demodulation, heterodyne detection, and optical power monitoring in WDM communication channels.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.015
GPT teacher head0.237
Teacher spread0.221 · 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

Citations14
Published2020
Admission routes2
Has abstractyes

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