Imperfect phase randomization and generalized decoy-state quantum key distribution
Bibliographic record
Abstract
Decoy-state methods are essential to perform quantum key distribution (QKD) at large distances in the absence of single-photon sources. However, the standard techniques apply only if laser pulses are used that are independent and identically distributed. Moreover, they require that the laser pulses are fully phase randomized. However, realistic high-speed QKD setups do not meet these stringent requirements. In this work, we generalize decoy-state analysis to accommodate laser sources that emit imperfectly phase-randomized states. We also develop theoretical tools to prove the security of protocols with lasers that emit pulses that are independent, but not identically distributed. These tools can be used with recent work [G. Curr\'as-Lorenzo, S. Nahar, N. L\"utkenhaus, K. Tamaki, and M. Curty, Quantum Sci. Technol. (2023)] to prove the security of laser sources with correlated phase distributions as well. We quantitatively demonstrate the effect of imperfect phase randomization on key rates by computing the key rates for a simple implementation of the three-state protocol.
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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".