Robotized polarization characterization platform for free-space quantum communication optics
Bibliographic record
Abstract
We develop a polarization characterization platform for optical devices in free-space quantum communications. We demonstrate an imaging polarimeter, which analyzes both incident polarization states and the angle of incidence, attached to a six-axis collaborative robot arm, enabling polarization characterization at any position and direction with consistent precision. We present a detailed description of each subsystem, including the calibration and polarization-test procedure, and analyze polarization measurement errors caused by imperfect orientations of the robot arm using a Mueller-matrix model of polarimeters at tilt incidence. We perform a proof-of-principle experiment for an angle-dependent polarization test for a commercial silver-coated mirror for which the polarization states of the reflected light can be accurately calculated. Quantitative agreement between the theory and experiment validates our methodology. We demonstrate the polarization test for a 20.3 cm lens designed for a quantum optical transmitter in Canada's Quantum Encryption and Science Satellite mission.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".