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Record W1985951294 · doi:10.1364/ls.2013.lw1g.3

Raman Scattering for Quantum Technologies

2013· article· en· W1985951294 on OpenAlexaff
Duncan England, Philip J. Bustard, J. Nunn, Benjamin Sussman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNeural Networks and Reservoir Computing
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsQuantum technologyQuantum imagingQuantum sensorQuantum networkQuantum information scienceOpen quantum systemQuantum cryptographyQuantum computerComputer scienceQuantumPhysicsPhotonicsQuantum simulatorQuantum opticsQuantum informationQuantum mechanicsQuantum entanglement

Abstract

fetched live from OpenAlex

Quantum mechanics has remained one of the most fascinating topics in physics ever since it was first formalized by the Copenhagen interpretation in the 1920’s. While much of the early experimental work focused on verification of quantum mechanical theory, focus has now shifted towards utilizing the remarkable features of quantum mechanics in emerging quantum technologies. For example, the evolution of complex quantum-mechanical systems could be used to perform calculations beyond the capability of classical computers and the inherent randomness involved in making measurements on a quantum state provides a source of unbreakable cryptographic keys for secure communications. In this talk, we introduce a high-speed quantum random number generator based on integrated photonics, and a high-bandwidth quantum memory for light; we will discuss the impact of these technologies on long-distance quantum communication and local photonic quantum processing.

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: Methods · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score0.231

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 science0.0010.000
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 head0.017
GPT teacher head0.232
Teacher spread0.215 · 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
GenreMethods

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

Citations0
Published2013
Admission routes1
Has abstractyes

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