Attosecond wave-packet interferometry using two-color XUV pulses
Bibliographic record
Abstract
We generate two attosecond pulse trains ($\mathrm{XU}{\mathrm{V}}_{\ensuremath{\omega}}$ and $\mathrm{XU}{\mathrm{V}}_{2\ensuremath{\omega}}$) by focusing an infrared (IR, $\ensuremath{\omega}$) laser pulse and its temporally advanced second harmonic field ($2\ensuremath{\omega}$) into an argon gas jet. Using the two XUV pulses and another infrared pulse, we perform two types of experiments for electron wave-packet interferences with attosecond time resolution. The delays between three pulses, $\mathrm{XU}{\mathrm{V}}_{2\ensuremath{\omega}}$, $\mathrm{XU}{\mathrm{V}}_{\ensuremath{\omega}}$, and IR, are independently controlled. First, at a fixed delay between the $\mathrm{XU}{\mathrm{V}}_{2\ensuremath{\omega}}$ and the IR pulses, we record the velocity map images of photoelectrons ionized from helium as a function the two XUV pulses. The photoelectron signal intensity is modulated with the period corresponding to the energy separation between the $1s\phantom{\rule{0.28em}{0ex}}\mathrm{and}\phantom{\rule{0.28em}{0ex}}4p$ states of helium, 174 as. This indicates that the $4p$ Rydberg state is populated by harmonic 15 ($15\ensuremath{\omega}$) in both $\mathrm{XU}{\mathrm{V}}_{2\ensuremath{\omega}}$ and $\mathrm{XU}{\mathrm{V}}_{\ensuremath{\omega}}$ pulses. Second, we overlap $\mathrm{XU}{\mathrm{V}}_{2\ensuremath{\omega}}$ with the IR pulse in time and record the VMI images as a function of the two pulses. By analyzing the interference pattern in the VMI images, we find that harmonic 13 (13 $\ensuremath{\omega}$) from $\mathrm{XU}{\mathrm{V}}_{2\ensuremath{\omega}}$ is responsible for the generation of the $g$ wave in the ionization continuum. Our method of using two XUV pulses containing different sets of harmonics can simplify attosecond XUV interferometry experiments.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".