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Classically simulating quantum circuits is crucial when developing or testingquantum algorithms. Due to the underlying exponential complexity, efficientdata structures are key for performing such simulations. To this end, tensornetworks and decision diagrams have independently been developed with differingperspectives, terminologies, and backgrounds in mind. Although this leftdesigners with two complementary data structures for quantum circuitsimulation, thus far it remains unclear which one is the better choice for agiven use case. In this work, we (1) consider how these techniques approachclassical quantum circuit simulation, and (2) examine their (dis)similaritieswith regard to their most applicable abstraction level, the desired simulationoutput, the impact of the computation order, and the ease of distributing theworkload. As a result, we provide guidelines for when to better use tensornetworks and when to better use decision diagrams in classical quantum circuitsimulation.

Tensor Networks or Decision Diagrams? Guidelines for Classical Quantum Circuit Simulation