Pre-Privacy Amplification: A Post-Processing Technique for Quantum Key Distribution with Application to the Simplified Trusted Relay
Bibliographic record
Abstract
Until quantum repeaters and quantum error correcting codes can be made commercially \nviable, long distance quantum key distribution (QKD) will continue to rely on trusted \nrelay satellites. Strongly constrained by weight and power efficiency, little room is left \nfor raw computational power, lowering the key rate per second. Efforts to reduce the \ncomputational burden on satellites, such as the simplified trusted relay (which does \nnot participate in privacy amplification), come at a significant cost to their key rate per \nbit sent and maximum tolerable error rate. We construct a post processing technique, \nthat acts as a sort of pre-privacy amplification that is performed before the usual error \ncorrection and privacy amplification steps. Loosely speaking, it provides a way to scale \nbetween the simplified trusted relay and the usual full trusted relay. For the asymptotic \nqubit six-state protocol, we demonstrate an increase in the maximum tolerable error rate \nfrom ∼12.62% to ∼12.83% for the full trusted relay, and from ∼9.05% to ∼11.7% for the \nsimplified trusted relay. We also provide several sufficient conditions to determine when \nunique reduction matrices will yield identical key rates.
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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 | 0.001 | 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".