International Journal on Magnetic Particle Imaging IJMPI
Vol. 12 No. 1 Suppl 1 (2026): Int J Mag Part Imag
https://doi.org/10.18416/IJMPI.2026.2603013
Proceedings Articles, ID 1030
Reduced-Order Modeling of Nanoparticle Magnetization Dynamics
Main Article Content
Copyright (c) 2026 Sevil Dilge Gulsun, Asli Alpman, Emine Ulku Saritas

This work is licensed under a Creative Commons Attribution 4.0 International License.
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.
Article Details
References
brown–néel-rotation. Physics in Medicine Biology, 63(3):035004,
2018, doi:10.1088/1361-6560/aaa186.
[2] A. Alpman, M. Utkur, and E. U. Saritas. Mnp characterization
and signal prediction using a model-based dictionary. International
Journal on Magnetic Particle Imaging, 8(1), 2022,
doi:10.18416/ijmpi.2022.2203017.
[3] T. Knopp, H. Albers, M. Grosser, M. Möddel, and T. Kluth. Exploiting
the fourier neural operator for faster magnetization
model evaluations based on the fokker–planck equation. International
Journal on Magnetic Particle Imaging, 9(1), 2023,
doi:10.18416/IJMPI.2023.2303003.
[4] M. H. Kayapinar, A. Alpman, and E. U. Saritas. Fourier neural
operator for coupled brown–neel rotation model. International
Journal on Magnetic Particle Imaging, 10(1), 2024,
doi:10.18416/ijmpi.2024.2403008.
[5] K. Kunisch and S. Volkwein. Galerkin proper orthogonal decomposition
methods for a general equation in fluid dynamics. SIAM
Journal on Numerical Analysis, 40(2):492–515, 2003.