Noise Transfer Characterization in Wavelength Conversion Based on Injection Locking in a Fabry–Perot Laser
Bibliographic record
Abstract
We evaluate the performance of wavelength conversion based on injection locking in a Fabry-Perot laser (FPL). We compare the bit error ratio (BER) of the original and the converted signals at different optical signal to noise ratios (OSNRs). We study experimentally both up- and down-conversion and show that wavelength conversion results in slight BER improvement. This is due to the FPL power transfer function and also absorption of TM polarization that results in noise reduction. Measurements of the noise histograms on "1" and "0" bits confirm noise compression after conversion. We also study the case of simultaneous dual-channel conversion (i.e., wavelength multi-casting) and compare it with the single channel case. The BER performance of the dual-channel case does not degrade compared to the input signal.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".