Proof-of-Principle Demonstration of Fully Passive Quantum Key Distribution
Bibliographic record
Abstract
Quantum key distribution (QKD) offers information-theoretic security based on the fundamental laws of physics. However, device imperfections, such as those in active modulators, may introduce side-channel leakage, thus compromising practical security. Attempts to remove active modulation, including passive decoy intensity preparation and polarization encoding, have faced theoretical constraints and inadequate security verification, thus hindering the achievement of a fully passive QKD scheme. Recent research [W. Wang et al., Phys. Rev. Lett. 130, 220801 (2023).PRLTAO0031-900710.1103/PhysRevLett.130.220801; 2V. Zapatero et al., Quantum Sci. Technol. 8, 025014 (2023).2058-956510.1088/2058-9565/acbc46] has systematically analyzed the security of a fully passive modulation protocol. Based on this, we utilize the gain-switching technique in combination with the postselection scheme and perform a proof-of-principle demonstration of a fully passive quantum key distribution with polarization encoding at channel losses of 7.2 dB, 11.6 dB, and 16.7 dB. Our work demonstrates the feasibility of active-modulation-free QKD in polarization-encoded systems.
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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".