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Record W2150299469 · doi:10.1038/srep02314

Inherent polarization entanglement generated from a monolithic semiconductor chip

2013· article· en· W2150299469 on OpenAlexaff
Rolf T. Horn, Piotr Kolenderski, Dongpeng Kang, Payam Abolghasem, Carmelo Scarcella, Adriano Della Frera, Alberto Tosi, L. G. Helt, Sergei V. Zhukovsky, J. E. Sipe, Gregor Weihs, Amr S. Helmy, Thomas Jennewein

Bibliographic record

VenueScientific Reports · 2013
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsUniversity of TorontoUniversity of Waterloo
Fundersnot available
KeywordsPhotonComputer scienceQuantum entanglementPhotonicsOptoelectronicsPolarization (electrochemistry)ScalabilityChipQuantumPhysicsOpticsElectronic engineeringTelecommunicationsQuantum mechanicsEngineeringChemistry

Abstract

fetched live from OpenAlex

Creating miniature chip scale implementations of optical quantum information protocols is a dream for many in the quantum optics community. This is largely because of the promise of stability and scalability. Here we present a monolithically integratable chip architecture upon which is built a photonic device primitive called a Bragg reflection waveguide (BRW). Implemented in gallium arsenide, we show that, via the process of spontaneous parametric down conversion, the BRW is capable of directly producing polarization entangled photons without additional path difference compensation, spectral filtering or post-selection. After splitting the twin-photons immediately after they emerge from the chip, we perform a variety of correlation tests on the photon pairs and show non-classical behaviour in their polarization. Combined with the BRW's versatile architecture our results signify the BRW design as a serious contender on which to build large scale implementations of optical quantum processing devices.

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 categoriesScholarly communication
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 score0.357
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.015
GPT teacher head0.219
Teacher spread0.203 · 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.

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

Citations108
Published2013
Admission routes1
Has abstractyes

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