An Ising machine based on networks of subharmonic electrical resonators

TL;DR

This paper demonstrates that networks of driven nonlinear electrical resonators can solve complex Ising optimization problems by minimizing the Hamiltonian, showing potential for unconventional computing platforms.

Contribution

It introduces a novel electronic oscillator network that encodes Ising spins via subharmonic responses and experimentally solves non-trivial optimization problems.

Findings

Successfully minimized Ising Hamiltonian on complex graphs

Experimental and theoretical results show qualitative agreement

Proposed platform can explore capabilities of unconventional computing

Abstract

We explore a case example of networks of classical electronic oscillators evolving towards the solution of complex optimization problems. We show that when driven into subharmonic response, a network of such nonlinear electrical resonators can minimize the Ising Hamiltonian on non-trivial graphs such as antiferromagnetically coupled rewired-M{\"o}bius ladders. In this context, the spin-up and spin-down states of the Ising machine are represented by the oscillators' response at the even or odd driving cycles. Our experimental setting of driven nonlinear oscillators coupled via a programmable switch matrix leads to a unique energy minimizer when one such exists, and probes frustration where appropriate. Theoretical modeling of the electronic oscillators and their couplings allows us to accurately reproduce the qualitative features of the experimental results. This suggests the promise of this setup as a prototypical one for exploring the capabilities and limitations of such an unconventional computing platform.