ROGUE WAVES IN SPATIALLY EXTENDED OPTICAL SYSTEMS
Bibliographic record
Abstract
Giant anomalous events may occur in systems characterized by many waves, with extremely high amplitude waves appearing with a probability much higher than expected for a random dynamics. Such rare, and giant, events are known to occur on the ocean surface and have been named, in that context, "rogue waves". We present here some recent experimental results on the statistical properties of giant optical waves, or "optical rogue waves", observed in spatially extended optical systems. We will present the main statistical features of such extreme events, then, based on both a linear and a nonlinear experiment, we will outline a way enabling us to identify two key ingredients at the origin of optical rogue waves, namely, granularity, that is, a minimal size of the individual light spots, and inhomogeneity, that is, clustering of the light spots into separate domains with different average intensities. In the linear experiment we measure also the statistics of the waiting times between successive rogue waves and we show that it follows a log-Poisson distribution, which is characteristics of event separation observed in cooperative, complex systems and in such different fields as geophysics and biology.
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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".