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Record W2755426386 · doi:10.1038/s41598-017-12455-8

High-performance silicon photonic tri-state switch based on balanced nested Mach-Zehnder interferometer

2017· article· en· W2755426386 on OpenAlexafffund
Zeqin Lu, D. Celo, Hamid Mehrvar, Éric Bernier, Lukas Chrostowski

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsHuawei Technologies (Canada)University of British ColumbiaUniversity of British Columbia Hospital
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOptical switchPhotonicsMach–Zehnder interferometerCrosstalkAstronomical interferometerInterferometrySilicon photonicsCrossover switchOptoelectronicsBlocking (statistics)Silicon on insulatorMaterials scienceComputer scienceSiliconOpticsPhysicsComputer network

Abstract

fetched live from OpenAlex

ABSATRCT: This work proposes a novel silicon photonic tri-state (cross/bar/blocking) switch, featuring high-speed switching, broadband operation, and crosstalk-free performance. The switch is designed based on a 2 × 2 balanced nested Mach-Zehnder interferometer structure with carrier injection phase tuning. As compared to silicon photonic dual-state (cross/bar) switches based on Mach-Zehnder interferometers with carrier injection phase tuning, the proposed switch not only has better performance in cross/bar switching but also provides an extra blocking state. The unique blocking state has a great advantage in applications of N × N switch fabrics, where idle switching elements in the fabrics can be configured to the blocking state for crosstalk suppression. According to our numerical experiments on a fully loaded 8 × 8 dilated Banyan switch fabric, the worst output crosstalk of the 8 × 8 switch can be dramatically suppressed by more than 50 dB, by assigning the blocking state to idle switching elements in the fabric. The results of this work can extend the functionality of silicon photonic switches and significantly improve the performance of on-chip N × N photonic switching technologies.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.013
GPT teacher head0.230
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 teacher head, 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

Citations35
Published2017
Admission routes2
Has abstractyes

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