Divergence‐free magnetic field interpolation and charged particle trajectory integration
Bibliographic record
Abstract
An interpolation method is presented for calculating a divergence‐free magnetic field at arbitrary locations in space from a representation of that field on a discrete grid. This interpolation method is used along with symplectic integration to perform particle trajectory integrations with good conservation properties. These integrations are better at conserving constants of motion and adiabatic invariants than standard, nonsymplectic Runge‐Kutta integration schemes. In particular, we verify that carrying out particle integrations with interpolated magnetic fields that satisfy ∇ · B = 0 yields a better conservation of the first adiabatic invariant μ. Comparisons are made between the different integration methods for proton trajectories in an ideal dipole magnetic field and in the cusp region of the magnetosphere as determined numerically from a global magnetohydrodynamic (MHD) model for realistic solar wind conditions. In the case considered, we find that particle trapping can occur in the cusp only if the self‐consistent electric field obtained from the MHD code is not taken into account. When that electric field is included in the calculation of particle trajectories, we fail to find any particle trapping in the cusp region.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".