Proposal and Validation of a Dual Scalable Annealing Processing System That Simultaneously Scales Capacity and Precision

Annealing processors (AP) specializing in solving combinatorial optimization problems have attracted attention. From the perspective of versatility, there has been a demand for fully-coupled Ising model-based AP, but challenges remain in achieving a system that combines both capacity (number of spins) and precision (interaction bit width) due to the complexity of the coupling. This study proposed a Dual Scalable Annealing Processing System (DSAPS) that can simultaneously scale the number of spins and interaction bit width using the same scalable structure. This introduces a new direction in scalability that combines both capacity and precision, compared to previous approaches that focused solely on capacity. A DSAPS with 2,048-spin and 10-bit interaction was implemented on an actual board. Four scaled MAX-CUT problems were used for operational validation, achieving accuracy of over 97 % compared with theoretical values. Compared to CPU simulation for a weighted MAX-CUT problem, the average cut value error was limited to 0.912 %. Furthermore, the average cut value of DSAPS was 2.93 % closer to that of CPU simulation than the 4 bit interaction board. These results confirm the utility of the proposed system and its new scaling direction.