Filter Design for SOA-Assisted SS-WDM Systems Using Parallel Multicanonical Monte Carlo
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Bibliographic record
Abstract
We address design and optimization of optical filters for spectrum-sliced wavelength division multiplexed (SS-WDM) systems employing saturated semiconductor optical amplifiers (SOAs) to suppress intensity noise. We study the impact of the shape of both slicing and channel selecting optical filters vis-a-vis two important impairments: the filtering effect and the crosstalk. The quantification of bit error rate (BER) is made possible by a parallel implementation of the multicanonical Monte Carlo algorithm. The intensity noise suppression by the SOA and signal degradation by subsequent optical filtering are studied both numerically and experimentally. We find optical filter shape and bandwidth that minimizes BER. By varying channel spacing and width, we estimate the achievable spectral efficiency when using both noise-cleaning SOA and forward error correction. We show that when constrained to use a symmetric architecture, i.e., identical filters for both slicing and channel selecting filters, there is a degradation in achievable spectral efficiency. We show that noise suppression is robust to variations in relative channel powers in multichannel systems. Our numerical simulations, vetted experimentally, provide accurate and quantitative results on optimized system performance.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it