Energy loss of ions and ion clusters in a disordered electron gas
Bibliographic record
Abstract
The various aspects of the correlated stopping power of pointlike and extended ions moving in a disordered degenerate electron gas have been analytically and numerically studied. Within the linear response theory we have made a systematic and comprehensive investigation of correlated stopping power, vicinage function, and related quantities for protons and extended ions, as well as for their clusters. The disorder, which leads to a damping of plasmons and quasiparticles in the electron gas, is taken into account through a relaxation time approximation in the linear response function. The stopping power for an arbitrary extended ion with a single bound electron is calculated in both the low- and high velocity limits. Our analytical results show that in a high velocity limit the main logarithmic contribution to the stopping power for an extended ion is significantly modified and for instance, in the case of He+, Li2+, and Be3+ ions must behave as ln ( A v(5) ), ln ( A v(3.25) ), and ln ( A v(2.77) ), respectively where v is the ion velocity. This behavior may be contrasted with the usual ln ( v(2) ) dependence for a point ion projectile. It is shown that the factor A which depends on the damping can be significantly reduced by increasing the latter. In order to highlight the effects of damping we present a comparison of our analytical and numerical results, in the case of both pointlike and extended ions, obtained for a nonzero damping with those for a vanishing damping.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".