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Record W2977897528 · doi:10.1021/acsphotonics.9b01026

Exploiting Long-Range Disorder in Slow-Light Photonic Crystal Waveguides: Anderson Localization and Ultrahigh <i>Q</i>/<i>V</i> Cavities

2019· article· en· W2977897528 on OpenAlexafffund

Bibliographic record

VenueACS Photonics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaQueen's University
KeywordsAnderson localizationScatteringPhotonic crystalPhotonicsFigure of meritWaveguideNonlinear opticsQuality (philosophy)

Abstract

fetched live from OpenAlex

The interplay between order and disorder in photonic lattices opens up a wide range of novel optical scattering mechanisms, cavity-mode resonances, and applications that can be obscured by typical ordered design approaches to photonics. Striking examples include Anderson localization, random lasers, and visible light scattering in biophotonic structures such as butterfly wings. In this work, we present a profound example of light localization in photonic crystal waveguides by introducing long-range correlated disorder. Using a rigorous three-dimensional Bloch mode expansion technique, we demonstrate how interhole correlations have a negative contribution to the total out-of-plane radiative losses, leading to a pronounced enhancement of the quality factor, Q, and Q / V cavity figures of merit in the long-range correlation regime. Subsequently, the intensity fluctuations of the system are shown to globally increase with the correlation length, highlighting the nontrivial role of long-range disorder on the underlying scattering mechanisms. We also explore the possibility of creating ultrahigh quality cavity modes via interhole correlations, which have various functionalities in chip-based nonlinear optics and waveguide cavity-quantum electrodynamics.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.800
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 studies0.0000.000
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 head0.006
GPT teacher head0.221
Teacher spread0.215 · 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 designObservational
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

Citations11
Published2019
Admission routes2
Has abstractyes

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