Neuromorphic computing approaches become increasingly important as we address future
needs for efficiently processing massive amounts of data. The unique attributes of quantum …

Abstract Domain walls (DWs) in magnetic nanowires are promising candidates for a variety
of applications including Boolean/unconventional logic, memories, in-memory computing as …

Traditional electronics employs charge currents to control and transmit information and
therefore suffer from energy dissipation due to electron scattering. In the past decade, spin …

Bilayers of Nd Co 5/Ni 8 Fe 2 can act as reconfigurable racetracks thanks to the parallel
stripe-domain configuration present in the hard magnetic material with weak perpendicular …

Random phenomena are ubiquitous in magnetism. They include, for example: the random
orientation of magnetization in an assembly of non-interacting isotropic magnets; arbitrary …

The impressive performance of artificial neural networks has come at the cost of high energy
usage and CO 2 emissions. Unconventional computing architectures, with magnetic systems …

The incorporation of randomness into stochastic computing can provide ample opportunities
for applications such as simulated annealing, non‐polynomial hard problem solving, and …

Precise control of magnetic domain wall (DW) motion is crucial for DW-based spintronic
devices. To date, artificially designed DW pinning sites, such as notch structures, have been …

Achieving thermal equilibrium in two-dimensional lattices of interacting nanomagnets has
been a key issue on the route to study exotic phases in artificial frustrated magnets. We …

Conventional Galton board is an iconic model in statistics to study the stochastic dynamics of
particle with ideal hypothesis of equal probability. To test this hypothesis, we introduce an …