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Phonon-Mediated Nonclassical Interference in Diamond

2016· article· en· W2516692773 on OpenAlexafffund
Duncan England, Kent Bonsma-Fisher, Jean-Philippe W. MacLean, Philip J. Bustard, Khabat Heshami, Kevin J. Resch, Benjamin Sussman

Bibliographic record

VenuePhysical Review Letters · 2016
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsUniversity of OttawaUniversity of WaterlooNational Research Council Canada
FundersIndustry CanadaNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and ScienceCanada Research ChairsCanada Foundation for Innovation
KeywordsPhysicsPhotonBeam splitterCoherence (philosophical gambling strategy)PhotonicsQuantum imagingQuantumOpticsInterference (communication)Quantum sensorSuperposition principleQuantum information scienceInterferometryQuantum technologyQuantum networkQuantum mechanicsQuantum entanglementOpen quantum systemComputer scienceLaserTelecommunications

Abstract

fetched live from OpenAlex

Quantum interference of single photons is a fundamental aspect of many photonic quantum processing and communication protocols. Interference requires that the multiple pathways through an interferometer be temporally indistinguishable to within the coherence time of the photon. In this Letter, we use a diamond quantum memory to demonstrate interference between quantum pathways, initially temporally separated by many multiples of the optical coherence time. The quantum memory can be viewed as a light-matter beam splitter, mapping a THz-bandwidth single photon to a variable superposition of the output optical mode and stored phononic mode. Because the memory acts both as a beam splitter and as a buffer, the relevant coherence time for interference is not that of the photon, but rather that of the memory. We use this mechanism to demonstrate nonclassical single-photon and two-photon interference between quantum pathways initially separated by several picoseconds, even though the duration of the photons themselves is just ∼250 fs.

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.014
GPT teacher head0.263
Teacher spread0.250 · 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

Citations14
Published2016
Admission routes2
Has abstractyes

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