Nonlinear systems for unconventional computing

TL;DR

This paper reviews nonlinear physical systems like oscillator networks and lasers used in unconventional computing, highlighting their potential for solving complex problems and inspiring new algorithms beyond traditional computers.

Contribution

It provides a comprehensive overview of physical systems and algorithms in unconventional computing, emphasizing their potential and recent developments.

Findings

Physical systems emulate spin Hamiltonians for optimization

Physical processes inspire new algorithms for hard problems

Hybrid architectures combining physical platforms and algorithms show promise

Abstract

The search for new computational machines beyond the traditional von Neumann architecture has given rise to a modern area of nonlinear science -- development of unconventional computing -- requiring the efforts of mathematicians, physicists and engineers. Many analogue physical systems including nonlinear oscillator networks, lasers, and condensates were proposed and realised to address hard computational problems from various areas of social and physical sciences and technology. The analogue systems emulate spin Hamiltonians with continuous or discrete degrees of freedom to which actual optimisation problems can be mapped. Understanding the underlying physical process by which the system finds the ground state often leads to new classes of system-inspired or quantum-inspired algorithms for hard optimisation. Together physical platforms and related algorithms can be combined to form a hybrid architecture that may one day compete with conventional computing. In this Chapter, we review some of the systems and physically-inspired algorithms that show such promise.