ﻻ يوجد ملخص باللغة العربية
Computational micromagnetics has become an essential tool in academia and industry to support fundamental research and the design and development of devices. Consequently, computational micromagnetics is widely used in the community, and the fraction of time researchers spend performing computational studies is growing. We focus on reducing this time by improving the interface between the numerical simulation and the researcher. We have designed and developed a human-centred research environment called Ubermag. With Ubermag, scientists can control an existing micromagnetic simulation package, such as OOMMF, from Jupyter notebooks. The complete simulation workflow, including definition, execution, and data analysis of simulation runs, can be performed within the same notebook environment. Numerical libraries, co-developed by the computational and data science community, can immediately be used for micromagnetic data analysis within this Python-based environment. By design, it is possible to extend Ubermag to drive other micromagnetic packages from the same environment.
Increased data gathering capacity, together with the spread of data analytics techniques, has prompted an unprecedented concentration of information related to the individuals preferences in the hands of a few gatekeepers. In the present paper, we sh
Fast computation of demagnetization curves is essential for the computational design of soft magnetic sensors or permanent magnet materials. We show that a sparse preconditioner for a nonlinear conjugate gradient energy minimizer can lead to a speed
An efficient method for the calculation of ferromagnetic resonant modes of magnetic structures is presented. Finite-element discretization allows flexible geometries and location dependent material parameters. The resonant modes can be used for a sem
In this paper we apply an extended Landau-Lifschitz equation, as introduced by Bav{n}as et al. for the simulation of heat-assisted magnetic recording. This equation has similarities with the Landau-Lifshitz-Bloch equation. The Bav{n}as equation is su
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-dependent problems in micromagnetism such as fast response curve estimat