Automated Adaptation and Stabilization of a Tunable WDM Polarization-Independent Receiver on Active Silicon Photonic Platform
Bibliographic record
Abstract
We demonstrate automated adaptation, and stabilization of a silicon photonic wavelength-division multiplexing (WDM), polarization-independent receiver. A two-channel, tunable WDM polarization-independent receiver is designed, and used to demonstrate automated WDM polarization control. Using a control algorithm based on Barzilai, and Borwein's two-point step size gradient descent method, we realize automated polarization adaptation, and wavelength stabilization for two arbitrarily polarized input data streams. 10 Gb/s on-off keying, and 20 Gb/s pulse-amplitude modulation 4-level formats are generated as the high-speed input data streams. In addition, we implement a long-duration experiment, in which we measure the bit-error-ratio for continuously varying polarization states, and changing chip temperatures. The experimental results show that, with the automated control, the WDM polarization-independent receiver can adapt, stabilize, and track the arbitrary input polarization states from a standard optical fiber into the transverse electric mode of a silicon waveguide, and simultaneously stabilize the transmitted wavelength channels at various chip temperatures. We also show how the presented WDM polarization-independent receiver scales with N channels, and propose an improved design for large-scale WDM applications.
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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 | 0.000 | 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) | 0.000 | 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".