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<p>Ising machines offer a paradigm shift from traditional computing methods, tackling complex combinatorial optimization problems (COPs). Despite the proliferation of various Ising machine implementations, their application to solve real-world COPs has been limited. Here, we introduce a high-performance optoelectronic Ising machine (OEIM), based on optoelectronic parametric oscillators, that represents a significant advancement in this field. With 4096 Ising spins, arbitrary coupling capabilities, and unparalleled long-term stability, our OEIM outperforms traditional computing approaches in both accuracy and speed. By solving the benchmark maximum cut problem, we demonstrate its superior performance. More importantly, we apply the OEIM to a real-world traffic optimization problem, using real traffic data and a classical traffic model, and achieve results that far surpass those of conventional computers. This work not only validates the OEIM’s capability to solve complex practical challenges but also heralds a new era in real-time traffic management, where high-performance optoelectronic Ising machines enable rapid and efficient solutions to critical societal issues.</p>

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Programmable optoelectronic Ising machine for optimization of real-world problems

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月1日

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  • Zhewen Hu,
  • Yanbo Ren,
  • Yao Meng,
  • Tiejun Wang,
  • Yanchen Jiang,
  • Miaomiao Wei,
  • Ye Xiao,
  • Zhentong Li,
  • Ming Li

摘要

Ising machines offer a paradigm shift from traditional computing methods, tackling complex combinatorial optimization problems (COPs). Despite the proliferation of various Ising machine implementations, their application to solve real-world COPs has been limited. Here, we introduce a high-performance optoelectronic Ising machine (OEIM), based on optoelectronic parametric oscillators, that represents a significant advancement in this field. With 4096 Ising spins, arbitrary coupling capabilities, and unparalleled long-term stability, our OEIM outperforms traditional computing approaches in both accuracy and speed. By solving the benchmark maximum cut problem, we demonstrate its superior performance. More importantly, we apply the OEIM to a real-world traffic optimization problem, using real traffic data and a classical traffic model, and achieve results that far surpass those of conventional computers. This work not only validates the OEIM’s capability to solve complex practical challenges but also heralds a new era in real-time traffic management, where high-performance optoelectronic Ising machines enable rapid and efficient solutions to critical societal issues.