Calculation of energy loss in antiproton collisions with many-electron systems using Ehrenfest's theorem
Bibliographic record
Abstract
Energy loss in collisions of charged projectiles with many-electron systems can be dealt with in time-dependent density functional theory by invoking Ehrenfest's theorem for the time evolution of expectation values of observables. We derive an exact expression for the evaluation of energy loss for systems described in a target reference frame, which is a functional of the electron density. Using an approximation scheme, we then apply the expression to antiproton-atom collisions at intermediate and high energies within the framework of the basis generator method. The calculations are performed within the semiclassical approximation for the nuclear motion, and a straight-line trajectory is employed. The energy loss is evaluated from an expectation value of the time derivative of the time-dependent projectile potential, and it avoids the problem of identifying the excited and ionized many-electron contributions in the many-electron wave function. There is also no need to invoke the independent-event model, since the calculations are performed within the framework of the independent-electron mean-field model. Detailed comparisons are provided for net ionization and total energy loss of antiprotons colliding with hydrogen, helium, neon, carbon, nitrogen, and oxygen. Reasonable agreement is found with the results from one-electron and two-electron calculations for atomic hydrogen and helium, and with experiment in the latter case. For the $\overline{p}\text{\ensuremath{-}}\mathrm{Ne}$ system at intermediate collision energies, we find discrepancies with previous work that included only single-electron transitions. The sequence of results for C, N, O, and Ne allows one to paint a consistent picture that awaits experimental verification.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".