Oscillator-based Ising Machine
Tianshi Wang, Jaijeet Roychowdhury

TL;DR
This paper demonstrates that Ising machines can be implemented using various nonlinear oscillators, enabling scalable, high-speed, low-power optimization solutions with improved performance over existing systems.
Contribution
It introduces a novel approach to realize Ising machines with almost any nonlinear oscillator, expanding the potential hardware platforms for combinatorial optimization.
Findings
Simulation results outperform state-of-the-art Ising machines on a 2000-variable benchmark.
Feasibility shown through hardware implementation and simulations.
Oscillator-based Ising machines are suitable for large-scale, high-speed, low-power applications.
Abstract
Many combinatorial optimization problems can be mapped to finding the ground states of the corresponding Ising Hamiltonians. The physical systems that can solve optimization problems in this way, namely Ising machines, have been attracting more and more attention recently. Our work shows that Ising machines can be realized using almost any nonlinear self-sustaining oscillators with logic values encoded in their phases. Many types of such oscillators are readily available for large-scale integration, with potentials in high-speed and low-power operation. In this paper, we describe the operation and mechanism of oscillator-based Ising machines. The feasibility of our scheme is demonstrated through several examples in simulation and hardware, among which a simulation study reports average solutions exceeding those from state-of-art Ising machines on a benchmark combinatorial optimization…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Advanced Memory and Neural Computing · Neural Networks and Reservoir Computing
