Reduced-Order Modeling of Nanoparticle Magnetization Dynamics

The coupled Brown-Néel rotation model formulates the nanoparticle magnetization dynamics as a system of ordinary differential equations that are computationally demanding to solve. In this work, we propose utilizing a proper orthogonal decomposition approach for reduced-order modeling of magnetization dynamics, providing significant computational speedup while preserving accuracy.

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Publication Details

Journal
Infinite Science GmbH
Published
2025-11-04
DOI
https://doi.org/10.18416/ijmpi.2026.2603013
Primary Topic
Model Reduction and Neural Networks
Type
article
Field-Weighted Citation Impact
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article

Reduced-Order Modeling of Nanoparticle Magnetization Dynamics

Asli Alpman, Sevil Dilge Gülsün, Emine Ulku Saritas
Infinite Science GmbH
Model Reduction and Neural Networks
article

Reduced-Order Modeling of Nanoparticle Magnetization Dynamics

Asli Alpman, Sevil Dilge Gülsün, Emine Ulku Saritas
article en

Abstract

The coupled Brown-Néel rotation model formulates the nanoparticle magnetization dynamics as a system of ordinary differential equations that are computationally demanding to solve. In this work, we propose utilizing a proper orthogonal decomposition approach for reduced-order modeling of magnetization dynamics, providing significant computational speedup while preserving accuracy.

Infinite Science GmbH
Bilkent University (TR), University of California, Berkeley (US)
Openalex Percentile: Top 24%
Model Reduction and Neural Networks
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