Maximizing atmospheric-disturbed fiber coupling efficiency with speckle-based phase retrieval and a single-pixel camera
Bibliographic record
Abstract
An approach to adaptive optics utilizing a single-pixel camera (SPC) is proposed to maximize fiber coupling efficiency at the receiver side of an optical satellite-to-ground link perturbed by atmospheric turbulence. Using a single-pixel wavefront sensor enables operation at longer optical wavelengths, such as near and far infrared, which have advantageous propagation characteristics for free space optical communication. In this approach, a focal plane intensity image of the atmospheric-disturbed wavefront is taken via an SPC using a compressed sensing technique. An iterative speckle-based phase retrieval algorithm is then applied to infer the phase distortion corrected by a deformable mirror in a feedback loop. This computational approach to inferring the phase of the wavefront overcomes the limitations of traditional Shack-Hartman-based approaches, which are difficult to implement at high speed and at the long infrared wavelengths proposed for future optical satellite communication downlinks. It has been shown that fiber coupling efficiency is increased from less than 5% to 40%-50% in medium-to-strong turbulence scenarios with the phase retrieval algorithm proposed in this work.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".