Quantum circuit compilers using gate commutation rules

Itoko, Toshinari; Raymond, Rudy; Imamichi, Takashi; Matsuo, Atsushi; Cross, Andrew W.

doi:10.1145/3287624.3287701

Cited by 39 publications

(31 citation statements)

References 16 publications

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“…In our recent paper, we argued about the drawback of resolving the two-qubit operations layer by layer in many existing approaches, and showed the importance of taking into account gate commutation rules [3]. We demonstrated how four simple commutation rules, which consists of commuting CNOT gates and/or single-qubit gates, can lead to quantum circuit mapping with significantly less number of additional SWAP gates.…”

Section: Introductionmentioning

confidence: 95%

“…3b. The dependency graphs with less commutation rules than those in [3] were first considered in [4]. Venturelli et al [18] considered commutation rules specific to their circuits of interest and proposed a solution based on a temporal planner; however, unlike our approaches, they did not provide systematic methods exploiting the rules.…”

Section: Motivation and Related Workmentioning

confidence: 99%

“…We first review the original heuristic algorithm [3], and then describe how to extend it to handle both SWAP and Bridge gates.…”

Section: Heuristic Algorithmmentioning

confidence: 99%

“…The average numbers of Bridge gates are stated in (·). The No-Bridge column lists the optimal numbers of SWAP gates from the original algorithm in [3]…”

Section: Comparison With Other Formulations Without Commutation Rulesmentioning

confidence: 99%

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Optimization of quantum circuit mapping using gate transformation and commutation

et al. 2020

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This paper addresses quantum circuit mapping for Noisy Intermediate-Scale Quantum (NISQ) computers. Since NISQ computers constraint two-qubit operations on limited couplings, an input circuit must be transformed into an equivalent output circuit obeying the constraints. The transformation often requires additional gates that can affect the accuracy of running the circuit. Based upon a previous work of quantum circuit mapping that leverages gate commutation rules, this paper shows algorithms that utilize both transformation and commutation rules. Experiments on a standard benchmark dataset confirm the algorithms with more rules can find even better circuit mappings compared with the previously-known best algorithms.

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Section: Introductionmentioning

confidence: 95%

Section: Motivation and Related Workmentioning

confidence: 99%

“…We first review the original heuristic algorithm [3], and then describe how to extend it to handle both SWAP and Bridge gates.…”

Section: Heuristic Algorithmmentioning

confidence: 99%

“…The average numbers of Bridge gates are stated in (·). The No-Bridge column lists the optimal numbers of SWAP gates from the original algorithm in [3]…”

Section: Comparison With Other Formulations Without Commutation Rulesmentioning

confidence: 99%

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Optimization of quantum circuit mapping using gate transformation and commutation

et al. 2020

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“…This problem: the mapping of quantum circuits into arbitrary quantum machines has been referred as quantum circuit placement [Maslov et al 2008]; mapping problem [Zulehner et al 2018]; circuit compilation [Itoko et al 2019] and qubit allocation [Siraichi et al 2018;Tannu and Qureshi 2019]. Henceforth, we shall adopt the latter terminology.…”

Section: Introductionmentioning

confidence: 99%

Qubit allocation as a combination of subgraph isomorphism and token swapping

Siraichi

Santos

Collange

et al. 2019

Proc. ACM Program. Lang.

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In 2016, the first quantum processors have been made available to the general public. The possibility of programming an actual quantum device has elicited much enthusiasm. Yet, such possibility also brought challenges. One challenge is the so called Qubit Allocation problem: the mapping of a virtual quantum circuit into an actual quantum architecture. There exist solutions to this problem; however, in our opinion, they fail to capitalize on decades of improvements on graph theory. In contrast, this paper shows how to model qubit allocation as the combination of Subgraph Isomorphism and Token Swapping. This idea has been made possible by the publication of an approximative solution to the latter problem in 2016. We have compared our algorithm against five other qubit allocators, all independently designed in the last two years, including the winner of the IBM Challenge. When evaluated in łTokyo", a quantum architecture with 20 qubits, our technique outperforms these state-of-the-art approaches in terms of the quality of the solutions that it finds and the amount of memory that it uses, while showing practical runtime. CCS Concepts: • Computer systems organization → Quantum computing; • Software and its engineering → Compilers; • Theory of computation → Parameterized complexity and exact algorithms.

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