Cost-minimizing distribution matching supporting net 800 Gbit/s PS-PAM transmission over 2 km using a 4-λ EML TOSA
Bibliographic record
Abstract
Probabilistic shaping (PS) allows tunable spectral efficiency that is suitable for realizing high throughput intra-data center transceivers. In this Letter, we integrate the cost-minimizing distribution matching (CMDM) in the probability amplitude shaping scheme to generate PS-PAM signals with ultra-short symbol block lengths for reduced serial processing delay. We detail the principle of CMDM and present two different methods of implementation. We demonstrate that CMDM enables the transmission of single wavelength net 200 Gbit/s PS-PAM-8 over 2 km of single-mode fiber (SMF). We show that similar performance is achievable using a constant composition distribution matcher, yet requiring 10 times longer symbol block lengths. We also report, to the best of our knowledge, the first demonstration of net 800 Gbit/s transmission over 2 km of SMF using a packaged 4 - λ electro-absorption modulated laser transmitter optical sub-assembly (TOSA).
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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 | 0.001 |
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".