Real-Time Modeling of Skyrmion Dynamics in Arbitrary 2D Spatially Dependent Pinning Potential Landscapes

Abstract Non-flat energy landscapes leading to localized pinning of skyrmions pose an unavoidable challenge for studies of fundamental 2D spin structure dynamics and applications. Accounting for pinning is a key requirement for predictive modeling of skyrmion systems, impacting the system’s dynamics and introducing randomizing effects. We image skyrmions using magneto-optical Kerr microscopy on a magnetic thin film and analyze their hopping dynamics within the non-flat energy landscape. To achieve a fully quantitative model, we utilize diffusion and dwell times at pinning sites in both experiment and a coarse-grained Thiele model to determine simulation parameters and extrapolate the pinning energy landscape into regions that cannot be sampled within reasonable experimental timespans. We show a direct conversion between simulation and experimental units, the missing key step previously preventing quantitative quasiparticle modeling. We demonstrate our approach’s predictive power and ability for predictive in-silico prototyping of skyrmion devices by measuring the density dependence of skyrmion diffusion, showing excellent agreement with simulation predictions.