论文标题
与特殊驱动器进行电路故障诊断的量子退火
Quantum Annealing with Special Drivers for Circuit Fault Diagnostics
论文作者
论文摘要
我们提出了一个非常通用的量子退火协议，以解决组合电路故障诊断（CCFD）问题，该问题将演变限制在有效诊断的空间中。这是通过使用特殊的本地驱动程序来完成的，该特殊本地驱动程序在可行配置的空间上诱导过渡图，该驱动器是常规和实例的每个给定电路拓扑独立的。对小实例的分析表明，能隙具有通用形式，并且最小间隙发生在进化的最后三分之一中。我们使用这些功能来构建改进的退火时间表，并通过封闭的系统模拟对其性能进行了基准测试。我们发现，退化可以帮助量子退火的性能，尤其是对于最小故障诊断中故障次数较高的实例。这与基于蛮力搜索的经典方法的性能形成鲜明对比，该方法用于大规模电路。
We present a very general construction for quantum annealing protocols to solve Combinational Circuit Fault Diagnosis (CCFD) problems that restricts the evolution to the space of valid diagnoses. This is accomplished by using special local drivers that induce a transition graph on the space of feasible configurations that is regular and instance independent for each given circuit topology. Analysis of small instances shows that the energy gap has a generic form, and that the minimum gap occurs in the last third of the evolution. We used these features to construct an improved annealing schedule and benchmarked its performance through closed system simulations. We found that degeneracy can help the performance of quantum annealing, especially for instances with a higher number of faults in their minimum fault diagnosis. This contrasts with the performance of classical approaches based on brute force search that are used in industry for large scale circuits.
