Temperature‐Sensitive Dual Dispersive Wave Generation of Higher‐Order Modes in Liquid‐Core Fibers
Bibliographic record
Abstract
Abstract The emission of resonant radiation from temporal solitary waves—also known as dispersive wave generation—allows efficient energy transfer to far‐distant spectral domains. This coherent radiation can deliver large spectral densities at selected wavelengths once control over the individual soliton is achieved. Here, the concepts of few‐mode operation and local temperature tuning are combined for precise steering of cascaded dispersive wave generation in liquid‐core optical fibers. By exciting higher‐order TM and TE modes with femtosecond pulses at 1600 nm, the generation of two dispersive waves tunable by up to 33 nm K −1 through adjusting a selected part of the waveguide is observed. Sophisticated soliton‐driven nonlinear dynamics arising from thermally transitioning from anomalous to all‐normal dispersion with temperature changes of only a few Kelvin have been found, including soliton steering, soliton breakdown, and soliton post‐fission tuning. All experimental results are verified by nonlinear simulations and semi‐analytic phase‐matching calculations, overall providing a cost‐effective and practical toolbox for discovering unexplored states of light as well as for developing dynamically tunable broadband light sources.
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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 | 0.000 | 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 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".