High-intensity high-order harmonic generation for attosecond autocorrelation measurements
Bibliographic record
Abstract
We demonstrate two methods of high-order harmonic generation, which has the potential of generating high-order harmonics with high intensities. The first method is solid surface harmonics. Using the second harmonic output of the 10 TW, 60 fs Ti:sapphire laser system at the INRS, we have observed multiple soft x-ray harmonics of the 397 nm pump laser. The highest order (23 rd harmonic at 17.3 nm) observed in our experiments are limited by the 17 nm absorption edge of the thick 1.6 μm Al foil, which is used to eliminate the high intensity pump laser. The second method is harmonics from an ablation plume generated using a relatively low intensity prepulse. We demonstrate the generation of up to the 63rd harmonics (X=12.6 nm) of a Ti:sapphire laser pulse (150 fs, 10 mJ), using pre-pulse (210 ps, 24 mJ) produced boron plasma as the nonlinear medium. The influence of various parameters on the harmonic conversion efficiency was analyzed. Typical conversion efficiencies were evaluated to be between 10 -4 (for third harmonic) and 10 -7 (within the plateau range).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".