Magpy: A C++ accelerated Python package for simulating magnetic nanoparticle stochastic dynamics

TL;DR

Magpy is an open-source C++-accelerated Python package designed for efficient simulation of magnetic nanoparticle dynamics using stochastic differential equations, enabling detailed analysis of magnetic behavior and heat dissipation.

Contribution

It introduces a fast, Python-accessible simulation tool for magnetic nanoparticles leveraging C++ optimization and parallelization, which was not previously available.

Findings

Efficient simulation of nanoparticle magnetic dynamics.

Capability to compute equilibrium and dynamic responses.

Open-source and easily integrable with Python workflows.

Abstract

Magpy is a C++ accelerated Python package for modelling and simulating the magnetic dynamics of nano-sized particles. Nanoparticles are modelled as a system of three-dimensional macrospins and simulated with a set of coupled stochastic differential equations (the Landau-Lifshitz-Gilbert equation), which are solved numerically using explicit or implicit methods. The results of the simulations may be used to compute equilibrium states, the dynamic response to external magnetic fields, and heat dissipation. Magpy is built on a C++ library, which is optimised for serial execution, and exposed through a Python interface utilising an embarrassingly parallel strategy. Magpy is free, open-source, and available on github under the 3-Clause BSD License.