Performance of quantum-dash mode-locked lasers (QD-MLLDs) for high-capacity coherent optical communications
Bibliographic record
Abstract
We investigate the capabilities and limitations of quantum-dash mode-locked lasers (QD-MLLDs) as optical frequency comb sources in coherent optical communication systems. We demonstrate that QD-MLLDs are on par with conventional single-wavelength narrow linewidth laser sources and can support high symbol rates and modulation formats. We manage to transmit 64 quadrature amplitude modulation (QAM) signals up to 80 GBd over 80 km of standard single-mode fiber (SSMF), which highlights the distinctive phase noise performance of the QD-MLLD. Using a 38.5 GHz (6 dB bandwidth) silicon photonic (SiP) modulator, we achieve a maximum symbol rate of 104 GBd with 16QAM signaling and a maximum net rate of 416 Gb/s per carrier in a single polarization setup and after 80 km-SSMF transmission. We also compare QD-MLLD performance with commercial narrow-linewidth integrable tunable laser assemblies (ITLAs) and explore their potential for use as local oscillators (LOs) and signal carriers. The QD-MLLD has 45 comb lines usable for transmission at a frequency spacing of 25 GHz, and an RF linewidth of 35 kHz.
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 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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".