Multieigenvalue Communication
Bibliographic record
Abstract
In the most general case, all three components-the discrete eigenvalues, the discrete spectral amplitudes, and the continuous spectrum-of the nonlinear Fourier transform of a signal can be independently modulated. This paper examines information transmission using only the discrete eigenvalues, and presents heuristic designs for multisoliton signal sets with spectral efficiencies greater than 3 b/s/Hz. The first design, called multieigenvalue position encoding, is based on an exhaustive search followed by pruning of the signal set to remove high pulsewidth or high bandwidth outliers. The second design, called trellis encoding, achieves comparable efficiencies to the fist method at much lower complexity. These multisoliton signals do not undergo any pulse broadening, but are significantly limited by bandwidth expansion if the system length is not much smaller than the dispersion length parameter. This limitation suggests that modulating the eigenvalues alone cannot address the problem of nonlinearity in commercial fiber transmission systems, and that our proposed methods are only meaningful when dispersion is very small and dominated by nonlinearity, e.g., close to the zero-dispersion wavelength at 1300 nm.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".