Ultrafast laser filamentation control techniques for remote applications
Bibliographic record
Abstract
Two methods of filamentation control for remote applications were studied. The first one consisted in an adaptive optic system, implemented in a specially designed focusing beam expander, which corrected for wavefront aberrations. Using this setup we are able to generate extraordinarily strong nitrogen signals at a distance as far as 90 m using 40 mJ laser pulses. Moreover, the filaments produced were used in a remote sensing scheme to detect and identify multiple targets such as trace hydrocarbon gases, solid metallic targets and aqueous aerosol clouds. The other method consists in a filament regularization method where a circular aperture of variable diameter is centered on the laser propagation axis, prior to filamentation. Longer filaments with higher ionization densities were produced in air and studied via the backscattered N2 fluorescence. 3D + time stochastic numerical simulations has shown that the optimum aperture size corresponds to the case of multiple filament ‘squeezing’ around the propagation axis forming the regularized elongated structure with higher overall amount of plasma.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".