Effects of tampering on rare-gas core-shell clusters irradiated by resonantly tuned soft-x-ray pulses
Bibliographic record
Abstract
Tampering resonant rare-gas clusters with nonresonant atoms has been shown to significantly decrease in the final ionization of the resonant atoms [J. Phys. B: At., Mol. Opt. Phys. 41, 181001 (2008)], but not their transient ionization [Phys. Rev. Lett. 112, 183401 (2014)]. In this paper, we explain the details of the charge transfer mechanism from the resonant to nonresonant atoms. We have applied our model to the interaction of an ultraintense x-ray laser tuned to the center of xenon's giant 4d resonance with core-shell argon-xenon clusters. Our results are in agreement with previous experimental results of the disintegration products, and the transient states. Also, our model predicts that the resonant xenon is quickly ionized by the laser. The freed electrons then collisionally ionized the outer argon atoms before recombining with the inner xenon ions to reduce their final charge state. We find that unlike homogeneous clusters whose behavior is governed by the number of atoms, the behavior of core-shell heterogeneous clusters is well predicted by the ratio of resonant to nonresonant atoms.
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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".