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Emission-Frequency Separated High Quality Single-Photon Sources Enabled by Phonons

2019· article· en· W2954224532 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

VenuePhysical Review Letters · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsUniversity of Ottawa
FundersRussian Science FoundationDeutsche ForschungsgemeinschaftAlexander von Humboldt-Stiftung
KeywordsPhononLaserPhotonPhysicsExcitationAtomic physicsQuality (philosophy)OptoelectronicsOpticsCondensed matter physicsQuantum mechanics

Abstract

fetched live from OpenAlex

We demonstrate theoretically that the single-photon purity of photons emitted from a quantum dot exciton prepared by phonon-assisted off-resonant excitation can be significantly higher in a wide range of parameters than that obtained by resonant preparation for otherwise identical conditions. Despite the off-resonant excitation, the brightness stays on a high level. These surprising findings exploit the fact that the phonon-assisted preparation is a two-step process where phonons first lead to a relaxation between laser-dressed states while high exciton occupations are reached only with a delay to the laser pulse maximum by adiabatically undressing the dot states. Due to this delay, possible subsequent processes, in particular multiphoton excitations, appear at a time when the laser pulse is almost gone. The resulting suppression of reexcitation processes increases the single-photon purity. Due to the spectral separation of the signal photons from the laser frequencies this enables the emission of high quality single photons not disturbed by a laser background while taking advantage of the robustness of the phonon assisted scheme.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.376
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.015
GPT teacher head0.294
Teacher spread0.278 · 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