Controlling the polarization and phase of high-order harmonics with aplasmonic metasurface
Bibliographic record
Abstract
Nanostructured surfaces, or metasurfaces, allow exquisite control of linear and nonlinear optical processes by reshaping the amplitude, phase, and polarization of electric and magnetic fields near wavelength-scale heterogeneities. Recently, metasurfaces have broken new ground in high-field attosecond science where they have been utilized to amplify the emission of high-order harmonics of femtosecond infrared laser pulses, a notoriously inefficient process, by enhancing the incident field, and to shape the emitted high harmonics in space. Here we show control of the polarization and phase of high harmonics with a plasmonic metasurface. We design and fabricate perpendicularly aligned rectangular gold antennas on a silicon crystal that generate circularly polarized deep-ultraviolet high harmonics, from a circularly polarized infrared driver, providing a simple path for achieving circular emission from patterned crystals. Our metasurface enhances the circularly polarized harmonics up to ∼ 43 times when compared to the unpatterned surface, where harmonics are quenched. Looking forward, circularly polarized high harmonics will be useful tools for sensing chiral laser–matter interactions and magnetic materials. Our approach paves the way for polarization control at even shorter, extreme ultraviolet, wavelengths.
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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".