Strong multiple-capture effect in slow Ar<sup>17+</sup>–Ar collisions: a quantum mechanical analysis
Bibliographic record
Abstract
A recent x-ray spectroscopy experiment on Ar 17+ –Ar collisions at the velocity of 0.53 au provided evidence for strong multiple electron capture (Trassinelli et al 2012 J. Phys. B: At. Mol. Opt. Phys. 45 085202). We have investigated single and multiple captures in the same system by coupling a quantum-mechanical independent electron model calculation for the collision dynamics with a phenomenological Auger model to obtain n selective capture cross sections for n = 2 to n = 10. Using these cross sections and a radiative cascade scheme, we obtained x-ray emission intensities that can be compared with the experimental data. Good agreement is found for the Lyman series from n = 3 to n = 7 if the multiple capture contributions are included, whereas calculations that ignore them are in stark conflict with the measurements.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".