Software

magnum.np is a Python library for the solution of micromagnetic problems with the finite-difference method. It implements state-of-the-art algorithms and is based on pytorch, which allows to seamlessly run code either on GPU or on CPU. Simulation scripts are written in Python which leads to very readable yet flexible code. Due to pytorch integration, extensive postprocessing can be done directly in the simulations scripts. Furthermore pytorch's autograd feature makes it possible to solve inverse problems without significant modifications of the code. This manual is meant to give you both a quick start and a reference to magnum.np.

• magnum.np on Gitlab

This tool also runs entirely in the cloud, without any installation required. To run the mumag 4 standard problem, please click on the link below.

• magnum.np in the cloud (mumag 4 problem)

This interactive tool solves the Landau-Lifshitz-Gilbert equations using the finite difference method to simulate magnonic waveguides composed of different materials.

You can excite magnonic waveguides and visualize their dispersion relations and modes.
You can run the script by pressing "Ctrl + F9" (run all cells)
By clicking on a point on the dispersion relation in the colab notebook (left click), the corresponding mode will be visualized.

This tool runs entirely in the cloud, without any installation required.

• Dispersion solver on colab