Hot atom reaction yields in Mu*+H2 and T*+H2 from quasiclassical trajectory cross sections on the Liu–Siegbahn–Truhlar–Horowitz surface
Bibliographic record
Abstract
In order to provide an assessment of the “global” accuracy of the Liu–Siegbahn–Truhlar–Horowitz (LSTH) potential surface for H3, hot atom reaction yields, which are determined from collision processes over an energy range much wider than that of single-collision experiments, have been calculated for the Mu*+H2 and T*+H2 systems. The isotopic comparison of muonium (Mu=μ+e−), an ultralight isotope of hydrogen (mMu/mH≈1/9), with the heaviest H-atom isotope, tritium, is a novel approach in testing the global accuracy of the H3 surface. These reaction yields have been calculated using a formalism developed for (μ+) charge exchange, with input cross sections for elastic, inelastic (rovibrational excitation) and reactive collisions determined from quasi classical trajectories on the LSTH surface, in the center-of-mass energy range 0.5–11 eV. The rate of energy loss of the hot atom (Mu* or T*) due to elastic and inelastic collisions with the moderator (H2) drastically affects the hot atom reaction yield. In particular, the forwardness of the angular differential cross section for the elastic process plays a crucial role in determining the stopping power for hot atoms. Good agreement is obtained in the absolute yields for both Mu*+H2 and T*+H2, for the first time from microscopic cross sections, demonstrating that the LSTH surface remains surprisingly accurate over a wide range of energy and isotopic mass.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".