Enhanced phase-matching for generation of soft X-ray harmonics and attosecond pulses in atomic gases
Bibliographic record
Abstract
<a href="http://oe.osa.org/virtual_issue.cfm?vid=36">Focus Serial: Frontiers of Nonlinear Optics</a> We theoretically investigate the generation of high harmonics and attosecond pulses by mid-infrared (IR) driving fields. Conditions for coherent build-up of high harmonics are revisited. We show that the coherence length dictated by ionization-induced dephasing does not constitute an ultimate limitation to the coherent growth of soft X-ray (> 100 eV) harmonics driven by few-cycle mid-IR driving pulses: perfect phase-matching, similar to non-adiabatic self-phase- matching, can be achieved even without non-linear deformation of the driving pulse. Our trajectory-based analysis of phase-matching reveals several important advantages of using longer laser wavelengths: conversion efficiency can be improved by orders of magnitude, phase-matched build-up of harmonics can be achieved in a jet with a high gas pressure, and isolated attosecond pulses can be extracted from plateau harmonics.
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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 | 0.001 |
| 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".