Evaluation of the Impact of Filter Shape on the Performance of SOA-Assisted SS-WDM Systems Using Parallelized Multicanonical Monte Carlo
Bibliographic record
Abstract
We study the impact of the shape of optical filters on the bit error rate (BER) of a multi-channel spectrum-sliced wavelength division multiplexed (SS-WDM) system, incorporating nonlinear semiconductor optical amplifiers (SOA) to suppress the excess intensity noise, using a parallel implementation of Multicanonical Monte Carlo (MMC) algorithm. Both the slicing filter (SF) at the transmitter, and the channel selecting filter (CSF) at the receiver are allowed to be independently chosen from a reduced set of filter shapes. BER curves corresponding to a fixed SF bandwidth and bit-rate are traced for various bandwidths of the CSF. Both the single channel case, where the only impairment is the "filtering effect", and the multi-channel case, with crosstalk, are considered. We estimate the achievable spectral efficiency of SOA-assisted SS-WDM passive optical networks (PON) when both SOA-based intensity noise suppression, and forward error correction (FEC) are employed.
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 | 0.001 | 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".