Modeling satellite-Earth quantum channel downlinks with adaptive-optics coupling to single-mode fibers
Bibliographic record
Abstract
The efficient coupling of photons from a free-space quantum channel into a single-mode optical fiber (SMF) has important implications for quantum network concepts involving SMF interfaces to quantum detectors, atomic systems, integrated photonics, and direct coupling to a fiber network. Propagation through atmospheric turbulence, however, leads to wavefront errors that degrade mode matching with SMFs. In a free-space quantum channel, this leads to photon losses in proportion to the severity of the aberration. This is particularly problematic for satellite-Earth quantum channels, where atmospheric turbulence can lead to significant wavefront errors. This report considers propagation from low-Earth orbit to a terrestrial ground station and evaluates the efficiency with which photons couple either through a circular field stop or into an SMF situated in the focal plane of the optical receiver. The effects of atmospheric turbulence on the quantum channel are calculated numerically and quantified through the quantum bit error rate and secure key generation rates in a decoy-state BB84 protocol. Numerical simulations include the statistical nature of Kolmogorov turbulence, sky radiance, and an adaptive-optics system under closed-loop control.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".