Time-dependent electric field effect on the photodetachment dynamics of negative ions
Bibliographic record
Abstract
This paper addresses the photodetachment dynamics of a negative ion in a time-dependent electric field based on the semiclassical open-orbit theory. The photodetached electron probability density in a real time domain is studied in a gradient electric field for the first time. It is found that because of the influence of the gradient electric field, two or more electron trajectories can arrive at a given point on the detector, and the interference effect between these electron trajectories causes oscillatory structures in the electron probability density. Our calculation results suggest that when the external electric field changes very slowly with time, only two electron trajectories can arrive at a given point on the detector and the electron probability density exhibits a regular two-term oscillatory pattern. However, when the electric field changes quickly with time, four electron trajectories can reach the detector, which makes the oscillatory structures in the electron probability density become much more complicated. In addition, the electric field strength, photon energy, and the position of the detector can affect the electron probability density of this system sensitively. Our study provides a clear and intuitive picture for the photodetachment dynamics of the negative ion in the external electric field from a time-dependent viewpoint and may guide the future experimental researches on the photodetachment microscopy of negative ions in the time-dependent electric field.
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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 | 0.001 |
| 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 | 0.001 |
| 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".