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Record W2913827751 · doi:10.1364/josab.36.000646

Proposed narrowband biphoton generation from an ensemble of solid-state quantum emitters

2019· article· en· W2913827751 on OpenAlexaff
Heejeong Jeong, Shengwang Du, Na Young Kim

Bibliographic record

VenueJournal of the Optical Society of America B · 2019
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsUniversity of Waterloo
FundersHong Kong University of Science and TechnologyResearch Grants Council, University Grants Committee
KeywordsLaser linewidthNarrowbandCoherence (philosophical gambling strategy)PhotonPhysicsDephasingElectromagnetically induced transparencyQuantumQuantum technologyQuantum stateCoherence timeAtomic physicsOpticsQuantum mechanicsLaserOpen quantum system

Abstract

fetched live from OpenAlex

We explore a mechanism for producing time-frequency entangled photon pairs (termed a biphoton) from an ensemble of atom-like solid-state quantum emitters. Four distinct energy levels of the solid-state system render four spin-conserving optical transitions as observed in color centers. This feature opens up the possibility to generate a four-wave mixing biphoton based on an electromagnetic induced transparency (EIT) for long-coherence quantum communication as demonstrated in cold atomic systems. We propose a narrow EIT window below a lifetime-limited linewidth of a SiV− in diamond, assuming a few hundred MHz. Consequently, the EIT-induced narrowband guarantees biphoton coherence time to be at least a few tens of a nanosecond without a cavity. Assessing the criteria of solid-state parameters applicable to the existing biphoton model from cold atoms will accelerate solid-state biphoton source research. This study shows that a realization of negligible ground state dephasing of a solid-state sample will be a crucial step toward a solid-state biphoton generation for more than a 100 ns time scale with a subnatural atomic linewidth of a few MHz.

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 score0.002
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 communication0.0000.001
Open science0.0010.001
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 head0.011
GPT teacher head0.245
Teacher spread0.234 · 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

Citations5
Published2019
Admission routes1
Has abstractyes

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