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Record W2071647493 · doi:10.1088/1367-2630/15/5/055013

Efficient optical pumping and high optical depth in a hollow-core photonic-crystal fibre for a broadband quantum memory

2013· article· en· W2071647493 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNew Journal of Physics · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum optics and atomic interactions
Canadian institutionsNational Research Council Canada
FundersEngineering and Physical Sciences Research Council
KeywordsBroadbandPhysicsOptoelectronicsPhotonicsQuantumQuantum networkQuantum memoryHomogeneousOpticsQuantum computerQuantum mechanics

Abstract

fetched live from OpenAlex

The generation of large multiphoton quantum states-for applications in computing, metrology and simulation-requires a network of high-efficiency quantum memories capable of storing broadband pulses. Integrating these memories into a fibre offers a number of advantages towards realizing this goal: strong light-matter coupling at low powers, simplified alignment and compatibility with existing photonic architectures. Here, we introduce a large-core kagome-structured hollow-core fibre as a suitable platform for an integrated fibre-based quantum memory with a warm atomic vapour. We demonstrate, for the first time, efficient optical pumping in such a system, where 90 +/- 1% of atoms are prepared in the ground state. We measure high optical depths (3 x 10(4)) and narrow homogeneous linewidths (6 +/- 2 MHz) that do not exhibit significant transit-time broadening, showing that we can prepare a Lambda-level system in a pure state. Our results establish that kagome fibres are suitable for implementing a broadband, room-temperature quantum memory, as well as a range of nonlinear optical effects.

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.

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: Empirical
Teacher disagreement score0.681
Threshold uncertainty score0.633

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 head0.017
GPT teacher head0.265
Teacher spread0.248 · 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