Simulation Paths for Quantum Circuit Simulation With Decision Diagrams What to Learn From Tensor Networks, and What Not

Burgholzer, Lukas; Ploier, Alexander; Wille, Robert

doi:10.1109/tcad.2022.3197969

Cited by 7 publications

(2 citation statements)

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“…The MQT offers the classical quantum circuit simulator DDSIM that can be used to perform various quantum circuit simulation tasks based on using decision diagrams as a data structure. This includes strong and weak simulation [12,13,14], approximation techniques [15,16], noise-aware simulation [17,18,19], hybrid Schrödinger-Feynman techniques [20], support for dynamic circuits, the computation of expectation values [21], the simulation of mixeddimensional systems [22], and more [23,24,25,26]. Example 1.…”

Section: Classical Simulation Of Quantum Circuitsmentioning

confidence: 99%

“…Our overarching objective is to provide solutions for design tasks across the entire quantum software stack. This entails high-level support for end users in realizing their applications [6,7,8,9,10,11], efficient methods for the classical simulation [12,13,14,15,16,17,18,19,20,21,22,23,24,25,26], compilation [11,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46], and verification [47,48,49,50,51,52,53,54,…”

Section: Introductionmentioning

confidence: 99%

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The basis of design tools for quantum computing

Wille

Burgholzer

Hillmich

et al. 2022

Proceedings of the 59th ACM/IEEE Design Automation Conference

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Quantum computers promise to efficiently solve important problems classical computers never will. However, in order to capitalize on these prospects, a fully automated quantum software stack needs to be developed. This involves a multitude of complex tasks from the classical simulation of quantum circuits, over their compilation to specific devices, to the verification of the circuits to be executed as well as the obtained results. All of these tasks are highly non-trivial and necessitate efficient data structures to tackle the inherent complexity. Starting from rather straight-forward arrays over decision diagrams (inspired by the design automation community) to tensor networks and the ZX-calculus, various complementary approaches have been proposed. This work provides a look "under the hood" of today's tools and showcases how these means are utilized in them, e.g., for simulation, compilation, and verification of quantum circuits.

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