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Record W3097697691 · doi:10.1364/optica.400751

Superconducting nanowire single-photon detectors with 98% system detection efficiency at 1550  nm

2020· article· en· W3097697691 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

VenueOptica · 2020
Typearticle
Languageen
FieldEngineering
TopicNanowire Synthesis and Applications
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNanowireDetectorPhotonOptoelectronicsMaterials scienceSuperconductivityPhysicsOpticsCondensed matter physics

Abstract

fetched live from OpenAlex

Superconducting nanowire single-photon detectors (SNSPDs) are an enabling technology for myriad quantum-optics experiments that require high-efficiency detection, large count rates, and precise timing resolution. The system detection efficiencies (SDEs) for fiber-coupled SNSPDs have fallen short of theoretical predictions of near unity by at least 7%, with the discrepancy being attributed to scattering, material absorption, and other SNSPD dynamics. We optimize the design and fabrication of an all-dielectric layered stack and fiber coupling package in order to achieve <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mn>98.0</mml:mn> <mml:mo>±</mml:mo> <mml:mn>0.5</mml:mn> <mml:mi mathvariant="normal">%</mml:mi> </mml:math> SDE, measured for single-mode-fiber guided photons derived from a highly attenuated 1550 nm continuous-wave laser. This enforces a smaller bound on the scattering and absorption losses in such systems and opens the use of SNSPDs for scenarios that demand high-SDE for throughput and fidelity.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.607

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 head0.013
GPT teacher head0.168
Teacher spread0.156 · 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