Classically simulating quantum circuits is crucial when developing or testing quantum algorithms. Due to the underlying exponential complexity, efficient data structures are key for performing such simulations. To this end, tensor networks and decision diagrams have independently been developed with differing perspectives, terminologies, and backgrounds in mind. Although this left designers with two complementary data structures for quantum circuit simulation, thus far it remains unclear which one is the better choice for a given use case. In this work, we (1) consider how these techniques approach classical quantum circuit simulation, and (2) examine their (dis)similarities with regard to their most applicable abstraction level, the desired simulation output, the impact of the computation order, and the ease of distributing the workload. As a result, we provide guidelines for when to better use tensor networks and when to better use decision diagrams in classical quantum circuit simulation.
翻译:典型模拟量子电路在开发或测试量子算法时至关重要。 由于潜在的指数复杂性,高效的数据结构是进行这种模拟的关键。 为此,以不同的观点、术语和背景独立开发了高频网络和决策图。 虽然这让设计者留下了两个用于量子电路模拟的补充数据结构,但到目前为止,对于某个特定用途案例,哪一个是更好的选择仍然不清楚。 在这项工作中,我们 (1) 考虑这些技术如何对待古典量子电路模拟,以及 (2) 检查这些技术在最适用的抽象水平、理想的模拟输出、计算顺序的影响以及工作量分配的便利性方面的(不同)差异。 因此,我们为何时更好地利用高频网络以及何时在古典量子电路模拟中使用决策图提供了指南。