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Record W2081045836 · doi:10.1364/josab.28.000a38

Material slow light and structural slow light: similarities and differences for nonlinear optics [Invited]

2011· article· en· W2081045836 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Optical Society of America B · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum optics and atomic interactions
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsNonlinear systemKinematicsNonlinear opticsSlow lightOpticsPhotonicsNonlinear opticalWork (physics)Contrast (vision)Group velocityResonance (particle physics)Variety (cybernetics)PhysicsComputer sciencePhotonic crystalClassical mechanicsQuantum mechanicsArtificial intelligence

Abstract

fetched live from OpenAlex

There are two standard methods for controlling the group velocity of light. One makes use of the dispersive properties associated with the resonance structure of a material medium. The other makes use of structural resonances, such as those that occur in photonic crystals. Both procedures have proved useful in a variety of situations. In this work we contrast these two approaches, especially in terms of issues such as the kinematics of energy flow though the system and the resulting implications for the behavior of nonlinear optical processes in these situations. Stated differently, this paper addresses the question of when nonlinear optical processes are enhanced through use of slow-light interactions and when they are not.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score0.310

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 head0.013
GPT teacher head0.237
Teacher spread0.224 · 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