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Nonlinear Systems for Unconventional Computing

  • Kirill P. Kalinin
  • Natalia G. BerloffEmail author
Chapter
  • 173 Downloads
Part of the Nonlinear Systems and Complexity book series (NSCH, volume 32)

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 of 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.

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.University of CambridgeCambridgeUnited Kingdom
  2. 2.Skolkovo Institute of Science and Technology Russian FederationMoscowRussia

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