Spin–orbit torque (SOT) is an emerging technology that enables the efficient manipulation of
spintronic devices. The initial processes of interest in SOTs involved electric fields, spin …

Neuromorphic circuits emulating the bio‐brain functionality via artificial devices have
achieved a substantial scientific leap in the past decade. However, even with the advent of …

Magnonics addresses the physical properties of spin waves and utilizes them for data
processing. Scalability down to atomic dimensions, operation in the GHz-to-THz frequency …

Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented …

Reservoir computing (RC) has been considered as one of the key computational principles
beyond von-Neumann computing. Magnetic skyrmions, topological particle-like spin textures …

Spintronic nano-synapses and nano-neurons perform neural network operations with high
accuracy thanks to their rich, reproducible and controllable magnetization dynamics. These …

Photonic in-memory computing exhibits promising potential to address the inherent
limitations of traditional von Neumann architecture. In this study, we demonstrate a tantalum …

Nonlinear phenomena in physical systems can be used for brain-inspired computing with
low energy consumption. Response from the dynamics of a topological spin structure called …

Reservoir computing is a neuromorphic architecture that may offer viable solutions to the
growing energy costs of machine learning. In software-based machine learning, computing …

Self-assembly of nanoparticles by means of interparticle optical forces provides a
compelling approach toward contact-free organization and manipulation of nanoscale …