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Record W2128190246 · doi:10.1103/physreva.90.043808

Converting one photon into two via four-wave mixing in optical fibers

2014· article· en· W2128190246 on OpenAlexaff
Audrey Dot, Evan Meyer-Scott, Raja Ahmad, Martin Rochette, Thomas Jennewein

Bibliographic record

VenuePhysical Review A · 2014
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsMcGill UniversityUniversity of Waterloo
Fundersnot available
KeywordsPhotonPhysicsFour-wave mixingMixing (physics)QuantumOpticsNonlinear opticsQuantum opticsOptical fiberOptoelectronicsNonlinear systemQuantum mechanics

Abstract

fetched live from OpenAlex

Observing nonlinear optical quantum effects or implementing quantum information protocols using nonlinear optics requires moving to ever-smaller input light intensities. However, low light intensities generally mean weak optical nonlinearities, which are inadequate for many applications. Here we calculate the performance of four-wave mixing in various optical fibers for the case where one of the input beams is a single photon. We show that in tapered chalcogenide glass fibers (microwires) a single photon plus strong pump beam can produce a pair of photons with a probability of 0.1%, much higher than in previous work on bulk and wave-guided crystal sources. Such a photon converter could be useful for creating large entangled photon states, for performing a loophole-free test of Bell's inequalities, and for quantum communication.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.866
Threshold uncertainty score0.448

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 communication0.0000.000
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 head0.025
GPT teacher head0.283
Teacher spread0.258 · 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 designSimulation or modeling
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

Citations18
Published2014
Admission routes1
Has abstractyes

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