Simulations of magnetic hysteresis loops at high temperatures
Bibliographic record
Abstract
The kinetic Monte-Carlo algorithm as well as standard micromagnetics are used to simulate MH loops of high anisotropy magnetic recording media at both short and long time scales over a wide range of temperatures relevant to heat-assisted magnetic recording. Microscopic parameters, common to both methods, were determined by fitting to experimental data on single-layer FePt-based media that uses the Magneto-Optic Kerr effect with a slow sweep rate of 700 Oe/s. Saturation moment, uniaxial anisotropy, and exchange constants are given an intrinsic temperature dependence based on published atomistic simulations of FePt grains with an effective Curie temperature of 680 K. Our results show good agreement between micromagnetics and kinetic Monte Carlo results over a wide range of sweep rates. Loops at the slow experimental sweep rates are found to become more square-shaped, with an increasing slope, as temperature increases from 300 K. These effects also occur at higher sweep rates, typical of recording speeds, but are much less pronounced. These results demonstrate the need for accurate determination of intrinsic thermal properties of future recording media as input to micromagnetic models as well as the sensitivity of the switching behavior of thin magnetic films to applied field sweep rates at higher temperatures.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".