Complete Nuclear Dipolar Line Shapes for High Transverse Field μSR
Bibliographic record
Abstract
It is common in analysis of transverse field TF-μSR data to assume that the line shape contribution of the nuclear spin lattice is Gaussian. Yet, evaluation of the muon-nuclear dipolar Hamiltonian is trivial in the high field limit subject to conditions of the TF-μSR experiment. Here we clarify the experimental requirements needed to satisfy the high field limit, and point the reader to previously published calculations in this regime. We describe our calculation method and present line shapes for the tetrahedral and octahedral sites in copper for external magnetic field directions parallel to the method of Van Vleck. As illustrated by the calculated line shapes, dipolar broadening at the muon site is highly sensitive to the direction of the external magnetic field. Judicious choice of the external field direction can be used to minimize dipolar broadening and departures of the line shape from a gaussian character. The calculation is a valuable tool to predict field dependence for a given muon site. Alternatively, it may be used to determine the muon site from experimental data obtained at various field orientations. In situations where the line shape is not well fit by a Gaussian and/or where the muon induces lattice distortion, the calculation is a valuable tool to better fit the μSR data.
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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 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".