Waveguide integrated superconducting single-photon detectors implemented as near-perfect absorbers of coherent radiation
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".