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Record W1868970192 · doi:10.1038/ncomms9233

Waveguide integrated superconducting single-photon detectors implemented as near-perfect absorbers of coherent radiation

2015· article· en· W1868970192 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

VenueNature Communications · 2015
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSuperconductivityPhotonDetectorRadiationPhysicsWaveguideOptoelectronicsOpticsCondensed matter physics

Abstract

fetched live from OpenAlex

At the core of an ideal single-photon detector is an active material that absorbs and converts every incident photon to a discriminable signal. A large active material favours efficient absorption, but often at the expense of conversion efficiency, noise, speed and timing accuracy. In this work, short (8.5 μm long) and narrow (8 × 35 nm2) U-shaped NbTiN nanowires atop silicon-on-insulator waveguides are embedded in asymmetric nanobeam cavities that render them as near-perfect absorbers despite their small volume. At 2.05 K, when biased at 0.9 of the critical current, the resulting superconducting single-photon detectors achieve a near-unity on-chip quantum efficiency for ∼1,545 nm photons, an intrinsic dark count rate <0.1 Hz, a reset time of ∼7 ns, and a timing jitter of ∼55 ps full-width at half-maximum. Such ultracompact, high-performance detectors are essential for progress in integrated quantum optics. A large volume of active material in a single-photon detector enhances absorption efficiency at the expense of conversion efficiency, noise and speed. Here the authors overcome this tradeoff in a near-perfect absorber architecture for a waveguide-integrated superconducting nanowire single-photon detector.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score0.581

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 integrity0.0000.001
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 head0.036
GPT teacher head0.295
Teacher spread0.259 · 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