Bibliographic record
Abstract
Materials that have hysteretic response to an external field are essential in modern information storage and processing technologies. A myriad of magnetization curves of several natural and artificial materials have previously been measured and each has found a particular mechanism that accounts for it. However, a phenomenological model that captures all the hysteresis loops and at the same time provides a simple way to design the magnetic response of a material while remaining minimal is missing. Here, we propose and experimentally demonstrate an elementary method to engineer hysteresis loops in metamaterials built out of dipolar chains. We show that by tuning the interactions of the system and its geometry we can shape the hysteresis loop which allows for the design of the softness of a magnetic material at will. Additionally, this mechanism allows for the control of the number of loops aimed to realize multiple-valued logic technologies. Our findings pave the way for the rational design of hysteretical responses in a variety of physical systems such as dipolar cold atoms, ferroelectrics, or artificial magnetic lattices, among others.
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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) | 0.000 | 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 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".