Mode-Locking and Noise Characteristics of InAs/InP Quantum Dash/Dot Lasers
Bibliographic record
Abstract
The mode-locking and noise characteristics of InP/InAs quantum dash (QDash) and quantum dot (QDot) multi-wavelength lasers, showing identical structural design, operating at the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</i> -band, are investigated and compared to each other. The QDash lasers exhibit improved repetition frequency stability with a lower threshold current and cavity loss. On the other hand, the QDot lasers show higher quality repetition frequency tunability with higher internal quantum efficiency, as well as lower average integrated relative intensity noise (RIN) and average optical linewidth. Furthermore, we demonstrate both the QDash and QDot lasers exhibit very clean constellation diagrams at 32 GBaud 16QAM base-band signal, while the QDot lasers’ bit-error ratio (BER) performance outperforms the QDashes. This finding highlights the viability of InAs/InP QDash/QDot lasers to be used as a low-cost optical source for large-scale networks.
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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 | 0.001 | 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".