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Record W2022900216 · doi:10.1109/3.890267

Multilevel infrared coupling of excitons in quantum-well semiconductors

2000· article· en· W2022900216 on OpenAlexaff
Seyed M. Sadeghi, J. Meyer, T. Tiedje, M. Beaudoin

Bibliographic record

VenueIEEE Journal of Quantum Electronics · 2000
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsUniversity of British ColumbiaUniversity of Toronto
Fundersnot available
KeywordsExcitonBiexcitonSpectral lineLaserMixing (physics)Atomic physicsCoupling (piping)SemiconductorResonance (particle physics)Quantum wellMaterials scienceInfraredPhotoluminescenceMolecular physicsPhysicsCondensed matter physicsOptoelectronicsOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

We study the effects of multilevel mixing of the 1s and 2s states of the E1-HH1 and E2-HH1 excitons in the emission spectra of an undoped quantum well. This is done by investigating the E1-HH1 exciton emission spectra in the presence of an intense CO/sub 2/ laser near resonance with the transition between El and E2. Our results show that, depending on the frequency of the CO/sub 2/ laser, these spectra are quenched peculiarly. We explain these phenomena based on the frequency dependence of the mixing configurations of the exciton states and infrared enhancement of the nonradiative decay rates of E1-HH1 excitons. We also study the effect of the nonparabolicity of the hole subband (HH1) in the infrared mixing of the E1-HH1 and E2-HH1 excitons.

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)0.000
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 score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.017
GPT teacher head0.276
Teacher spread0.260 · 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

Citations3
Published2000
Admission routes1
Has abstractyes

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