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Record W2016971153 · doi:10.1364/oe.18.002719

Cavity-QED assisted attraction between a cavity mode and an exciton mode in a planar photonic-crystal cavity

2010· article· en· W2016971153 on OpenAlexaff
Takehiko Tawara, H. Kamada, Takasumi Tanabe, Tetsuomi Sogawa, Hiroshi Okamoto, Peijun Yao, P. K. Pathak, Stephen Hughes

Bibliographic record

VenueOptics Express · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsQueen's University
Fundersnot available
KeywordsDephasingExcitonPhotoluminescenceOpticsOptical microcavityPhotonic crystalPlanarPhotonPhysicsBiexcitonSpontaneous emissionCoupling (piping)Resonance (particle physics)Materials scienceSpectral lineCavity quantum electrodynamicsMode volumeCondensed matter physicsAtomic physicsQuantumLaserQuantum mechanicsOptical fiber

Abstract

fetched live from OpenAlex

The photoluminescence spectra from a quantum-dot exciton weakly-coupled to a planar photonic-crystal cavity is experimentally investigated by temperature tuning. Significant resonance shifts of the cavity mode are observed as the cavity mode spectrally approaches that of the exciton mode, showing the appearance of cavity-to-exciton attraction or mode pulling. Cavity-mode spectral shifts are also found theoretically using a master equation model that includes incoherent pump processes for the coupled exciton and cavity, pure dephasing, and allows for photon emission via radiation modes and the leaky cavity mode. Both experiments and theory show clear cavity mode spectral shifts in the photoluminescence spectra, when certain coupling parameters are met. However, discrepancies between the experimental data and theory, including more pronounced spectral shifts in the measurements, indicate that other unknown mode-pulling effects may also be occurring.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.305
Teacher spread0.286 · 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 source (direct Gemma or distilled Codex), 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

Citations28
Published2010
Admission routes1
Has abstractyes

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