Karin Everschor-Sitte

Abstract Spin-based computing is emerging as a powerful approach for energy-efficient and high-performance solutions to future data processing hardware. Spintronic devices function by electrically manipulating the collective dynamics of the electron spin, which is inherently non-volatile, nonlinear and fast operating, and can couple to other degrees of freedom such as photonic and phononic systems.

Abstract Physical neuromorphic computing, exploiting the complex dynamics of physical systems, has seen rapid advancements in sophistication and performance. Physical reservoir computing, a subset of neuromorphic computing, faces limitations due to its reliance on single systems. This constrains output dimensionality and dynamic range, limiting performance to a narrow range of tasks.

Antiferromagnets offer much faster dynamics compared to their ferromagnetic counterparts but their order parameter is extremely difficult to detect and control. So far, controlling the Néel order parameter electrically is limited to only very few materials where Néel spin-orbit torques are allowed by symmetry.