Spectral Efficiency-Adaptive Optical Transmission Using Time Domain Hybrid QAM for <newline/>Agile Optical Networks
Bibliographic record
Abstract
We report the transmission of time domain hybrid QAM (TDHQ) signals for agile optical networks. A continuous tradeoff between spectral efficiency and achievable distance by mixing modulation formats including QPSK, 8QAM, and 16QAM is demonstrated in two scenarios: 1) 28 Gbaud non-return-to-zero (NRZ) signal for fixed 50 GHz grid systems; 2) superchannel transmission at date rates of up to 1.15 Tb/s and spectral efficiencies of up to 7.68 b/s/Hz. The TDHQ signal is generated using high-speed digital-to-analog converters (DACs) at the transmitter, and low-complexity digital signal processing (DSP) is proposed for processing the TDHQ signals at the receiver. Moreover, the nonlinearity tolerance of hybrid QAM signals with different configurations is investigated.
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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 | 0.000 |
| 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) | 0.001 | 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".