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：经典模拟量子电路在开发或测试量子算法时至关重要。由于底层存在指数级复杂度，高效的数据结构是执行此类模拟的关键。为此，张量网络和决策图分别基于不同的视角、术语和背景独立发展。尽管这为量子电路模拟提供了两种互补的数据结构，但迄今仍不清楚在特定用例中哪一种是更优选择。在本工作中，我们（1）研究这些技术如何实现经典量子电路模拟，并（2）考察它们在最适用的抽象层级、所需模拟输出、计算顺序的影响以及工作负载分配的便捷性等方面的（异）同。据此，我们提供在经典量子电路模拟中何时更适合使用张量网络、何时更适合使用决策图的指南。