Enhancing Efficiency in Continuous-Time Ising Machine Through Direct Current Comparison

Ising machines, which leverage natural computing, exhibit exceptionally fast annealing and low energy consumption, positioning them as promising solutions for combinatorial optimization problems. In particular, CMOS-compatible Ising machines offer significant advantages due to their cost-effective fabrication and scalability. This paper proposes a novel CMOS-compatible continuous-time Ising machine that performs natural iteration and optimization based on physical properties through direct current comparison. The architecture and circuit design enable rapid updates of Ising nodes via interactions within a resistive array, providing real-time feedback to other nodes and facilitating efficient annealing. Simulations under 65 nm process demonstrate that, for a 100-node fully connected Max-Cut problem, our design requires only 20 ns of annealing time and 0.23 nJ of energy, while achieving an average accuracy of 96%. Compared to a state-of-the-art approach, our design reduces time to solution and energy consumption by 9× and 51×, respectively.