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对于离散优化问题的纠辅助变量算法.

Lorenzo Fioroni1,2, Vincenzo Savona1,2

  • 1Laboratory of Theoretical Physics of Nanosystems, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland.

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概括
此摘要是机器生成的。

这项研究引入了一种新的启发量子化来解决复杂的离散优化问题的启发式启发式. 它提供了一种利用量子效应的可扩展方法,潜在地改进了大型应用的现有解决方案.

关键词:
信息理论和计算计算.量子物理学的量子物理学

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科学领域:

  • 计算物理 计算物理
  • 量子计算是一种量子计算.
  • 运营研究 运营研究

背景情况:

  • 离散优化问题广泛存在,但在计算上具有挑战性.
  • 经典物理启发的启发式常见,但量子化提供了一种新的方法.
  • 现有的量子回火硬件可用于模拟和数字设备.

研究的目的:

  • 开发一种新的启发式启发,灵感来自量子化.
  • 为了利用通用一致状态作为量子状态表示的变化Ansatz.
  • 为了使能量和梯度的有效计算能够进行大规模优化.

主要方法:

  • 开发了一种灵感来自量子解热的启发式启发式.
  • 作为参数化的变量替代品,使用了通用一致状态.
  • 分析了具有多项式复杂性的能量和梯度计算.
  • 在3D爱德华兹-安德森模型上进行基准标记.

主要成果:

  • 启发式允许分析计算能量和梯度的低多项式复杂性.
  • 该方法可扩展到数千次旋转的问题.
  • 一般化的连贯状态捕捉了重要的纠性质.
  • 在3D爱德华兹-安德森模型上,性能与其他流行的启发方式进行了比较.

结论:

  • 拟议的启发式提供了一个可扩展的方法来利用量子效应进行离散优化.
  • 这种方法有可能补充或增强传统的优化技术.
  • 它为解决大规模,复杂的优化挑战提供了一个有前途的途径.