A Josephson Parametric Oscillator-Based Ising Machine

TL;DR

This paper presents a scalable, low-power Josephson parametric oscillator-based tile structure for Ising machines, capable of solving complex optimization problems efficiently and compatible with large-scale quantum computing architectures.

Contribution

Introduces a superconductor-based JPO tile structure for Ising machines, demonstrating scalability, low power consumption, and compatibility with LHZ architecture.

Findings

Operates at 7.5GHz with significantly reduced power consumption

Validated through simulations in noisy environments

Matches analytical Hamiltonian solutions

Abstract

Ising machines have emerged as a promising solution for rapidly solving NP-complete combinatorial optimization problems, surpassing the capabilities of traditional computing methods. By efficiently determining the ground state of the Hamiltonian during the annealing process, Ising machines can effectively complement CPUs in tackling optimization challenges. To realize these Ising machines, a bi-stable oscillator is essential to emulate the atomic spins and interactions of the Ising model. This study introduces a Josephson parametric oscillator (JPO)-based tile structure, serving as a fundamental unit for scalable superconductor-based Ising machines. Leveraging the bi-stable nature of JPOs, which are superconductor-based oscillators, the proposed machine can operate at frequencies of 7.5GHz while consuming significantly less power (by three orders of magnitude) than CMOS-based systems. Furthermore, the compatibility of the proposed tile structure with the Lechner-Hauke-Zoller (LHZ) architecture ensures its viability for large-scale integration. We conducted simulations of the tile in a noisy environment to validate its functionality. We verified its operational characteristics by comparing the results with the analytical solution of its Hamiltonian model. This verification demonstrates the feasibility and effectiveness of the JPO-based tile in implementing Ising machines, opening new avenues for efficient and scalable combinatorial optimization in quantum computing.