In neuromorphic computing, artificial synapses provide a multi‐weight (MW) conductance
state that is set based on inputs from neurons, analogous to the brain. Herein, artificial …

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

Inspired by the parallelism and efficiency of the brain, several candidates for artificial
synapse devices have been developed for neuromorphic computing, yet a nonlinear and …

The spatiotemporal nature of neuronal behavior in spiking neural networks (SNNs) makes
SNNs promising for edge applications that require high energy efficiency. To realize SNNs …

Abstract Machine learning techniques are commonly used to model complex relationships
but implementations on digital hardware are relatively inefficient due to poor matching …

There are pressing problems with traditional computing, especially for accomplishing data-
intensive and real-time tasks, that motivate the development of in-memory computing …

Topological solitons are exciting candidates for the physical implementation of next-
generation computing systems. As these solitons are nanoscale and can be controlled with …

Layered two-dimensional (2D) magnet/semiconductor heterostructures combine spintronic
and optoelectronic properties of constituent materials, leading to new magneto-optical and …

Magnetic domain walls and skyrmions in thin film micro-and nanostructures have been of
interest to a growing number of researchers since the turn of the millennium, motivated by …

Quantum computers allow to solve efficiently certain problems that are intractable for
classical computers. For the realization of a quantum computer, a qubit design as the basic …