Nonequilibrium process of magnetization switching influenced by thermal spin fluctuations
Bibliographic record
Abstract
Abstract We present a systematic study of the dynamic behavior of nonequilibrium magnetization configurations with time‐resolved scanning Kerr microscope and micromagnetic modeling. The magnetization switching dynamics enters a fully dynamic regime when the external field conditions are changed much faster than the magnetization in the elements is able to respond. We observe that the dynamic pathway develops a complexity not seen in quasi‐static reversal, but still retains a high level of order with well‐developed dynamic domain patterns formed in response to sub‐nanosecond transitions of the external applied magnetic field pulse. An increasing complexity in the spatial structure of the evolution is found to accompany the increasing switching speed, when a ferromagnetic element is driven by progressively faster reversing fields applied anti‐parallel to the initial magnetization direction. The sensitive dependence of the nonequilibrium magnetization configurations on switching speed can be understood in terms of a dynamic exchange interaction of thermally excited spins; the coherent modulation of the spins is strongly dependent on the rise time of switching magnetic field pulses. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
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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 | 0.000 |
| 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 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".