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Record W4308344042 · doi:10.1063/5.0114124

A continuous model of magnetic moment distribution in a system with bilinear and biquadratic coupling

2022· article· en· W4308344042 on OpenAlexafffund
Pavlo Omelchenko, Elliot Wadge, Juliana Lisik, Erol Girt, B. Heinrich

Bibliographic record

VenueJournal of Applied Physics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBilinear interpolationContinuous modellingCoupling (piping)Magnetic momentBoundary value problemPhysicsMoment (physics)Statistical physicsApplied mathematicsMathematical analysisComputer scienceMathematicsClassical mechanicsCondensed matter physicsMaterials science

Abstract

fetched live from OpenAlex

In this paper, we present a continuous model as an analog to the discrete atomic model often used in the interpretation/analysis of magnetometry studies of magnetic structures with bilinear and/or biquadratic coupling. For a typical set of parameters, the continuous model is shown to be nearly indistinguishable from its discrete counterpart; validating it for data analysis purposes. Furthermore, we also find a very simple analytic expression which can approximately solve the continuous model and also provides insight into the behaviors of the magnetic moment within the magnetic structure. The main advantage of the continuous model is that numerically it can be solved as a boundary value problem, which can be significantly faster than the energy minimization required for the discrete model improving computational speed and allowing for much more rapid data analysis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.186
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2022
Admission routes2
Has abstractyes

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