标题： 用双稳极化子网络求解NP难问题 显示英文标题

标题： Solving NP-hard problems with bistable polaritonic networks

摘要： 一个由局部双稳态驱动耗散腔极化子组成的晶格被理论发现能够有效模拟伊辛模型，同时也能够实现有效的横向场。 我们对自旋玻璃问题的系统性能进行了基准测试，并研究了基态能量偏差和成功概率随系统大小的变化情况。 作为具体例子，我们考虑了嵌入在伊辛模型中的NP难问题，即图分割和背包问题。 我们发现局部双稳态极化子网络可以作为经典模拟器来解决优化问题，这可能在指数复杂度类中表现出改进。 显示英文摘要

摘要： A lattice of locally bistable driven-dissipative cavity polaritons is found theoretically to effectively simulate the Ising model, also enabling an effective transverse field. We benchmark the system performance for spin glass problems, and study the scaling of the ground state energy deviation and success probability as a function of system size. As particular examples we consider NP-hard problems embedded in the Ising model, namely graph partitioning and the knapsack problem. We find that locally bistable polariton networks act as classical simulators for solving optimization problems, which can potentially present an improvement within the exponential complexity class.