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Record W2766588262 · doi:10.1109/lpt.2017.2764450

Ultra Low Loss Waveguide Transitions for Reticle-Scale Silicon Nanophotonic Routing

2017· article· en· W2766588262 on OpenAlexafffund
Jia Jiang, Dominic Goodwill, Patrick Dumais, D. Celo, Chunshu Zhang, Ming Li, Yuming Wei, Fei Zhao, Wanyuan Liu, Xin Tu, Dongyu Geng, Éric Bernier

Bibliographic record

VenueIEEE Photonics Technology Letters · 2017
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsHuawei Technologies (Canada)
FundersCMC Microsystems
KeywordsNanophotonicsReticleOptoelectronicsWaveguideSiliconSilicon photonicsMaterials scienceRouting (electronic design automation)OpticsComputer sciencePhysicsComputer network

Abstract

fetched live from OpenAlex

We report compact and low loss silicon nanophotonic waveguide transitions, to connect different cross-sections of routing waveguide in large photonic integrated circuits. 25-μm-long tapers shaped as a stretched sinusoid had 0.029 ± 0.002 dB absolute loss between single-mode strip and multi-mode rib waveguides. 10-μm-long adapters of concave elliptic shape had 0.002 ± 0.001 dB absolute loss between singlemode strip and rib waveguides, the lowest reported loss for such adapters.

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 categoriesMeta-epidemiology (narrow)
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 score0.131
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.228
Teacher spread0.220 · 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.

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

Citations3
Published2017
Admission routes2
Has abstractyes

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