An Ultra Low Noise Telecom Wavelength Free Running Single Photon Detector Using Negative Feedback Avalanche Diode
Why this work is in the frame
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Bibliographic record
Abstract
It is challenging to implement genuine free running single photon detectors for the 1550 nm wavelength range with simultaneously high detection efficiency (DE), low dark noise, and good time resolution. We report a novel read out system for the signals from a negative feedback avalanche diode (NFAD)1–3 which allows useful op-eration of these devices at a temperature of 193 K and results in very low dark counts ( ∼ 100 CPS), good time jitter ( ∼ 30 ps), and good DE (∼10 %). We char-acterized two NFADs with a time correlation method using photons generated from weak coherent pulses (WCP) and photon pairs produced by spontaneous parametric down conversion (SPDC). The inferred detector efficiencies for both types of pho-ton sources agree with each other. The best noise equivalent power of the device is estimated to be 8.1 × 10−18 W · Hz−1/2, more than 10 times better than typical InP/InGaAs SPADs show in free running mode. The afterpulsing probability was found to be less than 0.1 % per ns at the optimized operating point. In addition, we studied the performance of an entanglement-based quantum key distribution (QKD) using these detectors and develop a model for the quantum bit error rate (QBER) that incorporates the afterpulsing coefficients. We verified experimentally that using these NFADs it is feasible to implement QKD over 400 km of telecom fibre. Our NFAD photon detector system is very simple, and is well suited for single-photon applications where ultra-low noise and free-running operation is required, and some afterpulsing can be tolerated.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 it