Quantum-beat photoelectron-imaging spectroscopy of Xe in the VUV
Bibliographic record
Abstract
Time-resolved pump-probe measurements of Xe, pumped at 133 nm and probed at 266 nm, are presented. The pump pulse prepared a long-lived hyperfine wave packet in the Xe $5{p}^{5}(^{2}P_{1/2}^{\ensuremath{\circ}})6s{\phantom{\rule{0.16em}{0ex}}}^{2}{[1/2]}_{1}^{\ensuremath{\circ}}$ manifold ($E=77\phantom{\rule{0.16em}{0ex}}185\phantom{\rule{0.16em}{0ex}}{\mathrm{cm}}^{\ensuremath{-}1}=9.57\phantom{\rule{0.16em}{0ex}}\mathrm{eV}$). The wave packet was monitored via single-photon ionization and velocity map photoelectron images were measured. The images provide angle- and time-resolved data which, when obtained over a large time window (900 ps), constitute a precision quantum-beat spectroscopy measurement of the hyperfine state splittings. Additionally, analysis of the full photoelectron image stack provides a quantum-beat imaging modality, in which the Fourier components of the photoelectron images correlated with specific beat components can be obtained. This may also permit the extraction of isotope-resolved photoelectron images in the frequency domain, in cases where nuclear spins (hence beat components) can be uniquely assigned to specific isotopes (as herein), and also provides phase information relating to the ionization dynamics. The information content of both raw and inverted image stacks is investigated, suggesting the utility of the Fourier analysis methodology in cases where images cannot be inverted.
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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) | 0.002 | 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".