arXiv subjects

Jonathan Maes

Publications and source records attributed to Jonathan Maes.

3 recordsLinked to original sources

arXiv2024

mumax+: extensible GPU-accelerated micromagnetics and beyond

We present mumax+, an extensible GPU-accelerated micromagnetic simulator with a Python user interface, to address the challenges posed by current magnetism research into systems with complex magnetic ordering and interfaces. It is a general solver for the space- and time-dependent evolution of the magnetization and related vector quantities, using finite difference discretization. Here, we present its application and design and discuss features not available in \mumaxthree{}, such as the modeling of antiferromagnets with magnetoelastic coupling. As an illustration of its capabilities, we use \mumaxp{} to simulate state of the art magnetic systems. Specifically, we demonstrate the current induced domain wall motion in a polycrystalline antiferromagnet, we simulate the working principle of a strain-driven antiferromagnetic racetrack memory and we reproduce experimentally observed domain structures in a non-collinear antiferromagnet.

cond-mat.mes-hall↗

arXiv2024

The design, verification, and applications of Hotspice: a Monte Carlo simulator for artificial spin ice

We present Hotspice, a Monte Carlo simulation software designed to capture the dynamics and equilibrium states of Artificial Spin Ice (ASI) systems with both in-plane (IP) and out-of-plane (OOP) geometries. An Ising-like model is used where each nanomagnet is represented as a macrospin, with switching events driven by thermal fluctuations, magnetostatic interactions, and external fields. To improve simulation accuracy, we explore the impact of several corrections to this model, concerning for example the calculation of the dipole interaction in IP and OOP ASI, as well as the impact of allowing asymmetric rather than symmetric energy barriers between stable states. We validate these enhancements by comparing simulation results with experimental data for pinwheel and kagome ASI lattices, demonstrating how these corrections enable a more accurate simulation of the behavior of these systems. We finish with a demonstration of `clocking' in pinwheel and OOP square ASI as an example of reservoir computing.

physics.comp-ph↗

arXiv2024

Perpendicular-anisotropy artificial spin ice with spontaneous ordering: a platform for neuromorphic computing with flexible timescales

Arrays of coupled nanomagnets have wide-ranging fundamental and practical applications in artificial spin ices, neuromorphic computing and spintronics. However, lacking in these fields are nanomagnets with perpendicular magnetic anisotropy with sufficient magnetostatic interaction. This would not only open up new possibilities for artificial spin ice geometries but also enable novel coupling methods for applications. Here we demonstrate a method to engineer the energy landscape of artificial spin lattices with perpendicular magnetic anisotropy. With this, we are able to realize for the first time magnetostatically-coupled 2D lattices of out-of-plane Ising spins that spontaneously order at room temperature on timescales that can be precisely engineered. We show how this property, together with straightforward electrical interfacing, make this system a promising platform for reservoir computing. Our results open the way to investigate the thermodynamics of out-of-plane magnetostatically coupled nanomagnet arrays with novel spin ice geometries, as well as to exploit such nanomagnet arrays in unconventional computing, taking advantage of the adjustable temporal dynamics and strong coupling between nanomagnets.

cond-mat.mes-hall↗