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A QUANTUM-WALK-BASED ALGORITHM FOR CLASSICAL OPTIMIZATION PROBLEMS

机译:经典问题的基于量子行走的算法

摘要

Example circuit implementations of Szegedy's quantization of the Metropolis-Hastings walk are presented. In certain disclosed embodiments, a quantum walk procedure of a Markov chain Monte Carlo simulation is implemented in which a quantum move register is reset at every step in the quantum walk. In further embodiments, a quantum walk procedure of a Markov chain Monte Carlo simulation is implemented in which an underlying classical walk is obtained using a Metropolis-Hastings rotation or a Glauber dynamics rotation. In some embodiments, a quantum walk procedure is performed in the quantum computing device to implement a Markov Chain Monte Carlo method; during the quantum walk procedure, an intermediate measurement is obtained; and a rewinding procedure of one or more but not all steps of the quantum walk procedure is performed if the intermediate measurement produces an incorrect outcome.
机译:呈现了塞格迪量化Metropolis-Hastings步道的示例电路实现。在某些公开的实施例中,实现了马尔可夫链蒙特卡罗模拟的量子游程程序,其中在量子游程的每个步骤处重置量子移动寄存器。在进一步的实施例中,实现了马尔可夫链蒙特卡罗模拟的量子步态过程,其中,使用大都会-哈丁斯旋转或格劳伯动力学旋转获得了基础的经典步态。在一些实施例中,在量子计算设备中执行量子行走程序以实现马尔可夫链蒙特卡罗方法;在量子行走过程中,获得中间测量值;如果中间测量结果不正确,则执行一个或多个但不是全部步骤的倒带过程。

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