Measurements of atmospheric background light in the urban area Waterloo and its impact on satellite QKD system performance
Bibliographic record
Abstract
Quantum Key Distribution (QKD) allows sharing encryption keys with information theoretic security. Satellitebased QKD can establish long distance links due to the quadratic transmission loss in free-space instead of the exponential transmission loss in optical fibers. Atmospheric background light plays an important role in the QKD scheme as it may significantly contribute to the system Quantum Bit Error Rate (QBER). Therefore, background light needs to be examined closely. Due to the high variability of atmospheric conditions, direct measurements of the background light under different meteorological conditions are the best option to properly characterize the effect. Current considerations are mainly limited to the analysis of cloud-free scenarios by simulation and by experiment. Links can also take place when the environment differs from this ideal condition. Measurement data was recorded in C-band at the campus of the University of Waterloo, Canada, during the day with clear sky and during sunset with clear sky and partly-clouded sky conditions. The measurement data is shown and compared to simulation results and to the measurement data taken in Oberpfaffenhofen, Germany. The impact of background light is discussed on a chosen reference scenario outlining the importance of detector gating time and end-to-end transmission loss when wanting to realize daylight QKD.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".