Quantum key distribution with dual detectors
Bibliographic record
Abstract
To improve the performance of a quantum-key-distribution (QKD) system, high speed, low dark count single photon detectors (or low-noise homodyne detectors) are required. However, in practice, a fast detector is usually noisy. Here, we propose a dual-detector method to improve the performance of a practical QKD system with realistic detectors: the legitimate receiver randomly uses either a fast (but noisy) detector or a quiet (but slow) detector to measure the incoming quantum signals. The measurement results from the quiet detector can be used to bound the eavesdropper's information, while the measurement results from the fast detector are used to generate a secure key. We apply this idea to various QKD protocols. Simulation results demonstrate significant improvements of the secure key rate in the lower loss regime in both Bennett-Brassard 1984 (BB84) protocol with ideal single photon source and Gaussian-modulated coherent states protocol; while for decoy-state BB84 protocol with weak coherent source, the improvement is moderate. We also discuss various practical issues in implementing the dual-detector scheme.
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How this classification was reachedexpand
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 | 0.001 |
| 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 teacher head, 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".