With the slowdown of Moore's law, many emerging electronic devices and computing
architectures have been proposed to sustain the performance advancement of computing …

Combinatorial optimization (CO) has a broad range of applications in various fields,
including operations research, computer science, and artificial intelligence. However, many …

In this paper, we report new results on a novel Ising machine technology for solving
combinatorial optimization problems using networks of coupled self-sustaining oscillators …

Abstract Ising Machines (IMs) have the potential to outperform conventional Von-Neuman
architectures in notoriously difficult optimization problems. Various IM implementations have …

Combinatorial optimization problems are difficult to solve due to the space explosion in an
exhaustive search. Using Ising model-based solvers can efficiently find near-optimal …

Oscillator-based Ising machines (OIMs) recently grow in interest. These OIMs can solve
combinatorial optimization problems formulated as an Ising model. The computation …

Neural networks are increasingly used to solve optimization problems in various fields,
including operations research, design automation, and gene sequencing. However, these …

Finding the ground state of an Ising model maps to certain classes of combinatorial
optimization problems. Currently, several physical systems, called Ising machines, are being …

Many combinatorial optimization problems can be mapped to finding the ground states of
the corresponding Ising Hamiltonians. The physical systems that can solve optimization …

Coupled oscillator-based Ising machines offer an efficient stochastic search-based
approach to solve NP-hard combinatorial optimization problems (Maximum Cut problem …