Optimizing multiple-control Toffoli quantum circuit design with constraint programming

Abstract 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.

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Publication Details

Journal
Constraints
Published
2026-07-18
DOI
https://doi.org/10.1007/s10601-026-09399-0
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00

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article

Optimizing multiple-control Toffoli quantum circuit design with constraint programming

Kevin Dalmeijer, Pascal Van Hentenryck, Jeenah Jung
Constraints
Quantum Computing Algorithms and Architecture
article

Optimizing multiple-control Toffoli quantum circuit design with constraint programming

Kevin Dalmeijer, Pascal Van Hentenryck, Jeenah Jung
article en

Abstract

Abstract 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.

Constraints
Georgia Institute of Technology (US)
National Science Foundation, Division of Civil, Mechanical and Manufacturing Innovation
Openalex Percentile: Top 6%
Quantum Computing Algorithms and Architecture
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