Oscillatory neural networks (ONNs) exhibit a high potential for energy-efficient computing. In
ONNs, neurons are implemented with oscillators and synapses with resistive and/or …

Abstract In the'Beyond Moore's Law'era, with increasing edge intelligence, domain-specific
computing embracing unconventional approaches will become increasingly prevalent. At …

Modern computers require an exponential increase in resources when solving
computationally hard problems, motivating the need for an alternative computing platform to …

The Ising model is of prime importance in the field of statistical mechanics. Here we show
that Ising-type interactions can be realized in periodically driven circuits of stochastic binary …

The standard van Neumann computer excels at many things. However, it can be very
inefficient in solving optimization problems with a large solution space. For that reason, a …

Volatile memristors are versatile devices whose operating mechanism is based on an abrupt
and volatile change of resistivity. This switching between high and low resistance states is at …

Memristive crossbars have been proposed as a promising pathway to enabling all-to-all
connections for a variety of applications. One such application is the latch-based dynamical …

Coherent Ising machines (CIMs), leveraging the bistable physical properties of coherent
light to emulate Ising spins, exhibit great potential as hardware accelerators for tackling …

We propose a model to estimate the energy barrier responsible for the hysteresis of the
thermally driven Mott phase transition. The fitting results are in good agreement with …

Approximation algorithms for computationally complex problems are of significant
importance in computing as they provide computational guarantees of obtaining practically …