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Record W3163359852 · doi:10.1063/5.0048728

Isolating and enhancing single-photon emitters for 1550 nm quantum light sources using double nanohole optical tweezers

2021· article· en· W3163359852 on OpenAlexafffund
Zohreh Sharifi, Michael Dobinson, Ghazal Hajisalem, Mirali Seyed Shariatdoust, Adriaan L. Frencken, Frank C. J. M. van Veggel, Reuven Gordon

Bibliographic record

VenueThe Journal of Chemical Physics · 2021
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhotonWavelengthOptical tweezersOptoelectronicsCommon emitterMaterials scienceErbiumSingle-photon sourceTrappingOpticsSpontaneous emissionAtom (system on chip)Quantum dotPhysicsLaserDoping

Abstract

fetched live from OpenAlex

Single-photon sources are required for quantum technologies and can be created from individual atoms and atom-like defects. Erbium ions produce single photons at low-loss fiber optic wavelengths, but they have low emission rates, making them challenging to isolate reliably. Here, we tune the size of gold double nanoholes (DNHs) to enhance the emission of single erbium emitters, achieving 50× enhancement over rectangular apertures previously demonstrated. This produces enough enhancement to show emission from single nanocrystals at wavelengths not seen in our previous work, i.e., 400 and 1550 nm. We observe discrete levels of emission for nanocrystals with low numbers of emitters and demonstrate isolating single emitters. We describe how the trapping time is proportional to the enhancement factor for a given DNH structure, giving us an independent way to measure the enhancement. This shows a promising path to achieving single emitter sources at 1550 nm.

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 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 score0.329
Threshold uncertainty score0.364

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 communication0.0000.001
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 head0.024
GPT teacher head0.249
Teacher spread0.225 · 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 teacher head, 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

Citations19
Published2021
Admission routes2
Has abstractyes

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