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Topological and conventional nanophotonic waveguides for directional integrated quantum optics

2024· article· en· W4399856297 on OpenAlexafffund
N. J. Martin, Mahmoud Jalali Mehrabad, Xizhong Chen, R. Dost, E. Nussbaum, D. Hallett, L. Hallacy, Andrew P. Foster, Edmund Clarke, Pallavi Patil, Stephen Hughes, Mohammad Hafezi, A. M. Fox, M. S. Skolnick, L. R. Wilson

Bibliographic record

VenuePhysical Review Research · 2024
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsQueen's University
FundersEngineering and Physical Sciences Research CouncilNatural Sciences and Engineering Research Council of Canada
KeywordsNanophotonicsIntegrated opticsPhysicsQuantum opticsQuantumOpticsOptoelectronicsTopology (electrical circuits)Quantum mechanicsEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Directionality in integrated quantum photonics has emerged as a promising route towards achieving scalable quantum technologies with nonlinearities at the single-photon level. Topological photonic waveguides have been proposed as a novel approach to harnessing such directional light-matter interactions on-chip. However, uncertainties remain regarding the strength of the directional coupling of embedded quantum emitters to topological waveguides in comparison to conventional line defect waveguides. In this work we present an investigation of directional coupling in a range of waveguides using a combination of experimental, theoretical, and numerical analyses. We quantitatively characterize the position dependence of the light-matter coupling on several topological photonic waveguides and benchmark their directional coupling performance against conventional line defect waveguides. We conclude that topological waveguides underperform in comparison to conventional line defect waveguides, casting their directional optics credentials into doubt. To demonstrate this is not a question of the maturity of the field; we show that state-of-the-art inverse design methods, while capable of improving the directional emission of these topological waveguides, still place them significantly behind the operation of a conventional (glide-plane) photonic crystal waveguide. Our results and conclusions pave the way towards improving the implementation of quantitatively predicted quantum nonlinear effects on-chip. Published by the American Physical Society 2024

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.896
Threshold uncertainty score0.338

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 communication0.0000.000
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 head0.082
GPT teacher head0.415
Teacher spread0.334 · 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 designTheoretical or conceptual
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

Citations18
Published2024
Admission routes2
Has abstractyes

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