Self-Healing Dynamically Controllable Micro-Comb
Bibliographic record
Abstract
Micro-resonator-based frequency combs, or micro-combs, have gained considerable interest in recent years due to their many potential applications such as high-speed communication systems, spectroscopy and ultrafast optical clocks [1]. Most micro-combs systems are based on laser pumped optical parametric oscillation and are typically non-self-starting, requiring a well-defined warm-up strategy involving smart control [2]. An alternative approach to micro-combs is represented by the Filter-Driven Four-Wave Mixing (FD-FWM) laser [3-5], based on a nonlinear micro-resonator nested in a main amplifying fibre cavity. Although this system has demonstrated self-starting regimes, stable operation typically imposes a strict relation between the minimum free-spectral range (FSR) of the main-cavity and the Q-factor of the micro-resonator. The use of longer main-cavity fibre lengths (highly desirable for several positive features, such as a larger gain) results in unrecoverable unstable regimes, i.e. in super-mode instability, which arises from the existence of many oscillating main-cavity modes within each micro-resonator resonance.
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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) | 0.001 | 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 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".