Circularly polarized molecular high-order harmonic generation in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msup><mml:msub><mml:mi mathvariant="normal">H</mml:mi><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub><mml:mrow><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math>with intense laser pulses and static fields
Bibliographic record
Abstract
Molecular high-order harmonic generation (MHOHG) by a combined intense circularly polarized laser pulse and static electric field has been studied from the appropriate time-dependent Schr\"odinger equation (TDSE) for the ${{\mathrm{H}}_{2}}^{+}$ molecular ion. It is found that for a particular static field strength derived from a classical model, efficient MHOHG spectra are obtained with maximum energy ${I}_{p}$ $+$ 9.05${U}_{p}$, where ${I}_{p}$ is the ionization potential and ${U}_{p}={E}_{0}^{2}/4{m}_{e}{\ensuremath{\omega}}_{0}^{2}$ is the ponderomotive energy at amplitude ${E}_{0}$ and frequency ${\ensuremath{\omega}}_{0}$ of the circularly polarized laser pulse. The static field controls recollision of the electron with parent ions and is confirmed by numerical solutions of the ${{\mathrm{H}}_{2}}^{+}$ TDSE at equilibrium. To produce circularly polarized MHOHG spectra, a combination of an elliptically polarized pulse and a static electric field is found to be most efficient. A time-frequency analysis obtained via Gabor transforms is employed to identify electron recollision times responsible for the generation of these high-order harmonics. It is found that only single recollision trajectories contribute to the circularly polarized harmonics, thus generating new sources for high-frequency circularly polarized attosecond pulses.
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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) | 0.008 | 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".