Architecture and protocols of the future European quantum key distribution network
Bibliographic record
Abstract
Abstract A point‐to‐point quantum key distribution (QKD) system takes advantage of the laws of quantum physics to establish secret keys between two communicating parties. Compared to the classical methods, such as public‐key infrastructures, QKD offers unconditional security, which makes it attractive for very high security applications. However, this unprecedent level of security is mitigated by the inherent constraints of quantum communications, such as the limited rates and ranges of an individual point‐to‐point QKD link. A QKD network, which can be built by combining multiple point‐to‐point QKD devices, can alleviate the constraints and enable point‐to‐multi‐point key distribution based on QKD technology. The European project, secure communication based on quantum cryptography (SeCoQC) aims at deploying a prototype QKD network, which will be demonstrated in September 2008, by developing the architecture and the protocols, as well as the specific hardware for long‐range QKD networks. This paper discusses the important aspects of the architecture and the network layer protocols of the SeCoQC QKD network. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".