In situ high-harmonic microscopy of a nanostructured solid
Bibliographic record
Abstract
Nanostructured optical surfaces allow exquisite control over linear and nonlinear light interactions, where the surface actively creates new frequencies up to high-order harmonics of an intense infrared driving laser field. The function and performance of these surfaces depend sensitively on the distribution of the high-harmonic fields in and between the nanostructured elements, as the high-harmonic wavelength becomes comparable to the nanoscale features of the surface. Imaging the nonlinear response at the active surface with nanometer resolution would greatly benefit the optimization of the metasurface's function. Here we demonstrate an approach to lensless imaging of extreme ultraviolet high harmonics that resolves the amplitude and phase of nonlinear polarization at the active nanostructured surface of an MgO crystal. Imaging the near-field distribution of high harmonics is the gateway to optimized functional high-harmonic metasurfaces and the integration of high harmonics on a chip.
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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) | 0.001 | 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".