Optimizing Multiple-Control Toffoli Quantum Circuit Design with Constraint Programming

Fuente: arXiv
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Autori principali: Jung, Jihye, Dalmeijer, Kevin, Van Hentenryck, Pascal
Natura: Preprint
Pubblicazione: 2024
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author Jung, Jihye
Dalmeijer, Kevin
Van Hentenryck, Pascal
author_facet Jung, Jihye
Dalmeijer, Kevin
Van Hentenryck, Pascal
contents As quantum technology advances, the efficient design of quantum circuits has become an important area of research. This paper provides an introduction to the MCT quantum circuit design problem for reversible Boolean functions with the necessary background in quantum computing to comprehend the problem. While this is a well-studied problem, optimization models that minimize the true objective have only been explored recently. This paper introduces a new optimization model and symmetry-breaking constraints that improve solving time by up to two orders of magnitude compared to earlier work when a Constraint Programming solver is used. Experiments with up to seven qubits and using up to 15 quantum gates result in several new best-known circuits, obtained by any method, for well-known benchmarks. Several in-depth analyses are presented to validate the effectiveness of the symmetry-breaking constraints from multiple perspectives. Finally, an extensive comparison with other approaches shows that optimization models may require more time but can provide superior circuits with optimality guarantees.
format Preprint
id arxiv_https___arxiv_org_abs_2404_14384
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimizing Multiple-Control Toffoli Quantum Circuit Design with Constraint Programming
Jung, Jihye
Dalmeijer, Kevin
Van Hentenryck, Pascal
Optimization and Control
Emerging Technologies
Quantum Physics
As quantum technology advances, the efficient design of quantum circuits has become an important area of research. This paper provides an introduction to the MCT quantum circuit design problem for reversible Boolean functions with the necessary background in quantum computing to comprehend the problem. While this is a well-studied problem, optimization models that minimize the true objective have only been explored recently. This paper introduces a new optimization model and symmetry-breaking constraints that improve solving time by up to two orders of magnitude compared to earlier work when a Constraint Programming solver is used. Experiments with up to seven qubits and using up to 15 quantum gates result in several new best-known circuits, obtained by any method, for well-known benchmarks. Several in-depth analyses are presented to validate the effectiveness of the symmetry-breaking constraints from multiple perspectives. Finally, an extensive comparison with other approaches shows that optimization models may require more time but can provide superior circuits with optimality guarantees.
title Optimizing Multiple-Control Toffoli Quantum Circuit Design with Constraint Programming
topic Optimization and Control
Emerging Technologies
Quantum Physics
url https://arxiv.org/abs/2404.14384