InAs/InP quantum dot coherent comb lasers and their applications in data centre and coherent communication systems
Bibliographic record
Abstract
Next generation short and long reach communication networks would be required to provide data rates of multiterabit/ s. Such high line rates are not feasible using a single wavelength channel. However, the multi-terabit/s transmission capacity can be achieved by utilising highly parallel wavelength division multiplexing (WDM), with tens or hundreds of channels, in combination with spectrally efficient advanced modulation formats. Quantum dot (QD) coherent comb lasers (CCLs) are promising light sources for Terabit/s dense-WDM optical coherent and data center networks because such monolithic QD-CCLs solve the obvious cost, power consumption and packaging problems by replacing many separate lasers for each channel by only a single semiconductor laser. Other advantages include compact size, simple fabrication, and the ability for hybrid integration with silicon substrates. Recent years we have successfully developed InAs/InP QD CCLs with repetition rates from 10 GHz to 1000 GHz and a total output power up to 50 mW per facet at room temperature. In this paper we have presented the design, growth, fabrication, electronic control and packaging of the QD CCLs. The key technical specifications include L-I-V curves, optical and RF beating spectra, relative intensity noise and optical phase noise of each individual wavelength channel, as well as timing jitter are investigated. Data bandwidth transmission capacity of 5.376 Terabit/s and 10.8 Terabit/s in the PAM-4 and 16-QAM modulation formats are demonstrated by using a single QD CCL chip with a channel spacing of 34.2 GHz after 25 km and 100 km of single-mode fiber transmission lines, respectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".