Airborne demonstration of a quantum key distribution receiver payload
Bibliographic record
Abstract
Abstract Satellite-based quantum terminals are a feasible way to extend the reach of quantum communication protocols such as quantum key distribution (QKD) to the global scale. To that end, prior demonstrations have shown QKD transmissions from airborne platforms to receivers on ground, but none have shown QKD transmissions from ground to a moving aircraft, the latter scenario having simplicity and flexibility advantages for a hypothetical satellite. Here, we demonstrate QKD from a ground transmitter to a receiver prototype mounted on an airplane in flight. We have specifically designed our receiver prototype to consist of many components that are compatible with the environment and resource constraints of a satellite. Coupled with our relocatable ground station system, optical links with distances of 3–10 km were maintained and quantum signals transmitted while traversing angular rates similar to those observed of low-Earth-orbit satellites. For some passes of the aircraft over the ground station, links were established within 10 s of position data transmission, and with link times of a few minutes and received quantum bit error rates typically ≈3%–5% , we generated secure keys up to 868 kb in length. By successfully generating secure keys over several different pass configurations, we demonstrate the viability of technology that constitutes a quantum receiver satellite payload and provide a blueprint for future satellite missions to build upon.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".