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Record W2094538549 · doi:10.1088/0953-4075/42/6/065503

Transparency in nanophotonic quantum wires

2009· article· en· W2094538549 on OpenAlexafffund
Mahi R. Singh

Bibliographic record

VenueJournal of Physics B Atomic Molecular and Optical Physics · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsPhotonic crystalBound stateCrystal (programming language)Condensed matter physicsResonance (particle physics)NanowirePhotonNanophotonicsPhotonicsElectromagnetically induced transparencyOpticsOptoelectronicsAtomic physicsQuantum mechanics

Abstract

fetched live from OpenAlex

We have studied the quantum optics of a photonic quantum nanowire doped with an ensemble of three-level nanoparticles.The wire is made from two photonic crystals A and B. Crystal A is embedded within crystal B and acts as a photonic nanowire.It is considered that the conduction band of crystal A lies below that of crystal B. As a result, photons are confined in crystal A and are reflected from crystal B. The bound states of the confined photons are calculated using the transfer matrix method.It is found that the number of bound states in the wire depends on the size of the wire and the energy difference between the conduction band extrema of crystals A and B. The absorption coefficient of the system has also been calculated using the Schrödinger equation method.It is considered that the nanoparticles interact with the photonic bound states.Numerical simulations show that when one of the resonance energies lies near the bound state, the system becomes transparent.However, when the resonance energy lies away from the bound state the crystal reverts to an absorbing state.Similarly, when the radius of the dielectric spheres is changed the location of the transparency peak is shifted.This means that the present system can be switched between two states by changing the size of the wire and the transition energy.These findings can be used to make new types of optical 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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.007
GPT teacher head0.248
Teacher spread0.241 · 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 designBench or experimental
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
Published2009
Admission routes2
Has abstractyes

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