Light interference detection on-chip by integrated SNSPD counters
Bibliographic record
Abstract
A SWIFTS device (Stationary Wave Integrated Fourier Transform Spectrometer) has been realized with an array of 24 Superconducting Nanowire Single Photon Detectors (SNSPD), on-chip integrated under a Si3N4 monomode rib-waveguide interferometer. Colored light around 1.55μm wavelength is introduced through end-fire coupling, producing a counter-propagative stationary interferogram over the 40nm wide, 120nm spaced, 4nm thick epi-NbN nanowire array. Modulations in the source bandwidth have been detected using individual waveguide coupled SNSPDs operating in single photon counting mode, which is a step towards light spectrum reconstruction by inverse Fourier transform of the stationary wave intensity. We report the design, fabrication process and in-situ measurement at 4.2K of light power modulation in the interferometer, obtained with variable laser wavelength. Such micro-SWIFTS configuration with 160nm sampling period over 3.84μm distance allows a spectral bandwidth of 2μm and a wavelength resolution of 170nm. The light interferences direct sampling ability is unique and raises wide interest with several potential applications like fringe-tracking, metrology, cryptography or optical tomography.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".