Flexible grid spacing using Nyquist-shaped channels for undersea transmission
Bibliographic record
Abstract
In this paper, we experimentally study DC-PM-BPSK, PM-QPSK, and PM-16QAM at 35 Gbaud for undersea transmission in a WDM environment with frequency spacing ranging from 50 GHz (DWDM) to 33 GHz (Super-Nyquist). The experimental study focuses on noise, linear cross-talk, and nonlinear tolerance in two undersea applications: (1) Legacy dispersion-managed submarine cables up to 5,000 km in length and (2) New uncompensated submarine cables up to 12,500 km in length. We experimentally demonstrate that a reduction in frequency spacing below the symbol rate can be achieved, and quantify the performance penalties. We also show a comparison of performance and reach between legacy dispersion-managed applications, and new uncompensated applications, as the frequency spacing is reduced below the symbol rate. It is shown that the constellation and line system dispersion map have a significant impact on the tolerance to linear and nonlinear interference generated by narrow frequency spacing.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".