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Record W3081770254 · doi:10.1063/5.0009717

Complete and robust light transfer in three-waveguide coupler by shortcut to adiabaticity

2020· article· en· W3081770254 on OpenAlexfundno aff
Wei Huang, Yun Chen, Xiaowei Qu, Shan Yin, Xintong Shi, Xianming Xiong, Wentao Zhang, Zujun Qin, Yuting Zhang

Bibliographic record

VenueAIP Advances · 2020
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsnot available
FundersNational Science and Technology Major ProjectNational Outstanding Youth Foundation of ChinaGuilin University of Electronic TechnologyNatural Science Foundation of Guangxi ProvinceNational Natural Science Foundation of ChinaUniversity of Guelph
KeywordsStimulated Raman adiabatic passageWaveguideAdiabatic processTransfer (computing)FabricationPhysicsOpticsOptoelectronicsComputer scienceQuantum mechanics

Abstract

fetched live from OpenAlex

A novel design for complete transfer and robust three-waveguide coupler is presented in this paper, which employs shortcut to adiabaticity (STA) based on stimulated Raman adiabatic passage (STIRAP). Most recently, some remarkable papers on STA of STIRAP [Phys. Rev. A 94(6), 063411 (2016) and Nat. Comm. 7, 12479 (2016)] have been proposed in both theoretical and experimental configurations. In this paper, we propose to design a novel three-waveguide coupler by employing STA based on STIRAP, which can achieve much shorter device length and also maintain the robust performance against perturbations on device geometry parameters compared to previous devices. This finding significantly improves the performance and fabrication of integrated optical devices to build up more compactable devices.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.466

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.019
GPT teacher head0.215
Teacher spread0.197 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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