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English(EN) Accelerating ground state search of spatial photonic Ising machines with genetic-simulated annealing hybrid algorithm

混合算法加速光子Ising机优化

研究人员开发了一种新颖的光学遗传-模拟退火混合算法,以提高空间光子Ising机(SPIMs)的速度和准确性。这种新方法结合了遗传算法的全局搜索能力和模拟退火的精细调整精度。实验和模拟表明,与单独使用遗传算法或模拟退火相比,这种混合方法在Max-Cut等复杂优化问题上能产生更优的结果。 AI

影响 引入了一种使用光学硬件解决复杂优化问题的高效方法,可能影响依赖此类计算的领域。

排序理由 详细介绍新算法和实验验证的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.LG 阅读 →

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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Ze Zheng, Ruhui Ni, Jingyi Zhao, Xiaojian Hu, Wen Jiang, Yuegang Li, Hang Xu, Tailong Xiao, Guihua Zeng ·

    Accelerating ground state search of spatial photonic Ising machines with genetic-simulated annealing hybrid algorithm

    arXiv:2605.23295v1 Announce Type: cross Abstract: Spatial photonic Ising machines (SPIMs) based on spatial light modulators (SLMs) have emerged as highly effective solvers for many tasks, including combinatorial optimization problems and spin-glass simulations. However, tradition…