Ising Machine Based on Electrically Coupled Spin Hall Nano-Oscillators

The Ising machine is an unconventional computing architecture that can be used to solve NP-hard combinatorial optimization problems more efficiently than traditional von Neumann architectures. Fast, compact oscillator networks that provide programmable connectivities among arbitrary pairs of nodes are highly desirable for the development of practical oscillator-based Ising machines. Here we propose using an electrically coupled array of gigahertz spin Hall nano-oscillators to realize such a network. By developing a general analytical framework that describes injection locking of spin Hall oscillators with large precession angles, we explicitly show the mapping between the coupled oscillators' properties and the Ising model. We integrate our analytical model into a versatile Verilog-A device that can emulate the coupled dynamics of spin Hall oscillators in circuit simulators. With this abstract model, we analyze the performance of the spin Hall oscillator network at the circuit level using conventional electronic components and considering phase noise and scalability. Our results provide design insights and analysis tools toward the realization of a CMOS-integrated spin Hall oscillator Ising machine operating with a high degree of time, space, and energy efficiency.

Automated summary

The Ising machine is an unconventional computing architecture that can solve combinatorial optimization problems more efficiently than traditional architectures. In this study, we propose using an array of gigahertz spin Hall nano-oscillators to create a fast and compact oscillator network. We develop an analytical framework to understand the relationship between the properties of the coupled oscillators and the Ising model, and integrate it into a versatile Verilog-A device for circuit-level performance analysis. Our research provides insights and tools for designing a CMOS-integrated spin Hall oscillator Ising machine with high efficiency in time, space, and energy.