A 2048-spin bulk acoustic wave Ising machine for number partitioning and Sudoku
2026-07-02 • Hardware Architecture
Hardware Architecture
AI summaryⓘ
The authors developed a new type of optical Ising machine that uses signals traveling through solid materials at microwave frequencies, making it more stable, energy-efficient, and compact than previous versions. Their design can handle over 2,000 spins with full connectivity and solves certain mathematical problems like MAX-CUT, number partitioning, and Sudoku quickly. Compared to earlier machines, theirs is much more temperature stable and performs as well or better on complex problems. This approach could lead to affordable and scalable computing devices for solving optimization tasks.
Ising machinetime-multiplexingbulk acoustic wave delay lineMAX-CUT problemnumber partitioningSudokuthermal stabilitymicrowave frequencyoptimization problemsbifurcation algorithm
Authors
Venkatesh Vadde, Roman Ovcharov, Victor H. González, Roman Khymyn, Artem Litvinenko, Johan Åkerman
Abstract
Optical coherent Ising machines based on time-multiplexing have demonstrated significant progress in terms of connectivity and spin scalability. However, they are constrained by large physical footprints, high power consumption, poor thermal stability, and high cost. Here, we present a time-multiplexed Ising machine leveraging propagating wave packets in solid-state delay lines at microwave frequencies, enabling thermally stable, robust, low-power, tabletop, and affordable design. We use two serially connected 20.5 MHz, 707 μs bulk acoustic wave delay lines supporting 2,048 spins. Our design provides all-to-all connectivity with 15-bit coupling resolution and finds approximate MAX-CUT solutions in 341 ms, potentially scalable to sub-ms by using higher frequency delay lines. Additionally, we demonstrate solutions to number partitioning and Sudoku problems. Compared with state-of-the-art Coherent Ising machines, our machine exhibits four orders of magnitude higher thermal stability. Against the simulated bifurcation algorithm, our design achieves comparable results on the MAX-CUT problem, while outperforming it on the more complex number-partitioning and Sudoku problems.