标题： 一种用于组合优化问题的Kerr孤子伊辛机 显示英文标题

标题： A Kerr soliton Ising machine for combinatorial optimization problems

摘要： 日益增长的数字计算扩展挑战促使了新的方法出现，特别是在通过模拟神经网络和组合优化问题的物理系统的动态演化。 虽然光是一种超高效的的信息载体，但其内在的弱光相互作用使得直接的信息处理难以实现。 最近，专门的非线性光子学为光场提供了新的控制，具有非凡的带宽、相干性以及非线性本征态如孤子之间的强相互作用的出现。 我们利用数百个Kerr非线性微谐振器孤子的集合，并实现一个模拟反馈网络，创建了一个具有完全可编程全连接相互作用的Ising机器。 通过增加自反馈，对角线相互作用，每个孤子表现出一种普遍的类似自旋的分岔。 利用整个孤子集合之间的这种相互作用谱，我们将Ising机器编码以解决基准布尔可满足性问题（SAT）。 均匀孤子相互作用与我们的Ising机器与高速数据互连的兼容性使复杂SAT问题的快速精确求解成为可能。 事实上，孤子特性使机器在单次反馈步骤中光学功率和时间使用之间的权衡被限制在约10 mW和1$\mu$s。 我们在超过100个随机生成的SAT实例上进行了超过10,000次试验，以评估Ising机器，证明了其超越基准数字SAT求解器性能的潜力。 我们的工作突显了光学非线性、超低损耗光子学和光电电路的融合，这些可以结合用于广泛的计算加速任务。 显示英文摘要

摘要： The growing challenges of scaling digital computing motivate new approaches, especially through the dynamical evolution of physical systems that mimic neural networks and combinatorial optimization problems. While light is a hyper efficient information carrier, intrinsically weak light interactions make direct information processing difficult to implement. Recently, specialized nonlinear photonics have opened new controls over light fields with extraordinary bandwidth, coherence, and the emergence of strong interactions among nonlinear eigenstates like solitons. We harness an ensemble of hundreds of Kerr-nonlinear microresonator solitons and implement an analog feedback network to create an Ising machine with fully programmable all-to-all interactions. By increasing the feedback for self, on-diagonal interactions, each soliton exhibits a universal spin-like bifurcation. Using this palette of interactions amongst the entire soliton ensemble, we encode the Ising machine to solve the benchmark Boolean satisfiability problem (SAT). The combination of uniform soliton interactions and the compatibility of our Ising machine with high-speed data interconnects enables rapid and precise solutions of complex SAT problems. Indeed, the soliton properties bound the tradeoff of optical power and time use by the machine at approximately 10 mW and 1 $\mu$s for a single feedback step. We performed >10,000 trials on more than 100 randomly generated SAT instances to evaluate the Ising machine, demonstrating the potential to exceed the performance of benchmark digital SAT solvers. Our work highlights the convergence of optical nonlinearity, ultralow loss photonics, and optoelectronic circuits, which can be combined for a wide range of computation-acceleration tasks.