activity
20072026
most citedRoadmap on Spin-Wave Computing

475 citations · 2.5k across the 93 of their papers we have counts for

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32 papers · 1 filter

physics.comp-ph2026

Perspective on Magnetic Nanoparticle Modeling: Interactions, Timescales and Regimes

Deniz Mostarac, Andrey A. Kuznetsov, Manuel Wolfschwenger +7

The response of magnetic nanoparticles (MNPs) to applied magnetic fields underpins a broad range of biomedical and technological applications. In this Perspective, we review the pr…

physics.comp-ph2025★ 4 cited

Efficient solution strategy to couple micromagnetic simulations with ballistic transport in magnetic tunnel junctions

Peter Flauger, Claas Abert, Dieter Suess

We present a computationally efficient strategy that allows to simulate magnetization switching driven by spin-transfer torque in magnetic tunnel junctions within a micromagnetic m…

physics.comp-ph2023★ 1 cited

magnum.np -- A PyTorch based GPU enhanced Finite Difference Micromagnetic Simulation Framework for High Level Development and Inverse Design

Florian Bruckner, Sabri Koraltan, Claas Abert +1

magnum.np is a micromagnetic finite-difference library completely based on the tensor library PyTorch. The use of such a high level library leads to a highly maintainable and exten…

physics.comp-ph2023★ 13 cited

Physics-informed machine learning and stray field computation with application to micromagnetic energy minimization

Sebastian Schaffer, Thomas Schrefl, Harald Oezelt +5

We study the full 3d static micromagnetic equations via a physics-informed neural network (PINN) ansatz for the continuous magnetization configuration. PINNs are inherently mesh-fr…

physics.comp-ph2021★ 10 cited

Proposal for a micromagnetic standard problem: domain wall pinning at phase boundaries

Paul Heistracher, Claas Abert, Florian Bruckner +2

We propose a novel micromagnetic standard problem calculating the coercive field for unpinning a domain wall at the interface of a multiphase magnet. This problem is sensitive to d…

physics.comp-ph2021★ 11 cited

Machine learning methods for the prediction of micromagnetic magnetization dynamics

Sebastian Schaffer, Norbert J. Mauser, Thomas Schrefl +2

Machine learning (ML) entered the field of computational micromagnetics only recently. The main objective of these new approaches is the automatization of solutions of parameter-de…