Optimal Multi-Bit Toffoli Gate Synthesis

Multi-bit Toffoli gates form an essential quantum gate class for quantum algorithms. They should be efficiently decomposed into elementary single- or multi-qubit quantum gates, such as CNOT, T, and Hadarmard, for a scalable implementation of a quantum algorithm. We propose an engineering method for...

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Main Authors: Young-Min Jun, In-Chan Choi
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10041026/
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author Young-Min Jun
In-Chan Choi
author_facet Young-Min Jun
In-Chan Choi
author_sort Young-Min Jun
collection DOAJ
description Multi-bit Toffoli gates form an essential quantum gate class for quantum algorithms. They should be efficiently decomposed into elementary single- or multi-qubit quantum gates, such as CNOT, T, and Hadarmard, for a scalable implementation of a quantum algorithm. We propose an engineering method for the practical synthesis of a multi-bit Toffoli gate. Two optimization models and their closed-form solutions are presented for optimal decomposition of the multi-bit Toffoli gate. These models are based on linearized multi-objective integer programming with parameters such as the number of target ancillae, ancillae states, and basis gates. The proposed method supports the systematic handling of quantum circuit constraints, including the total number of available qubits and maximum circuit depth, which depend on various quantum hardware specifications. Our approach exhibits promise in the noisy intermediate-scale quantum environment by providing a rapid and optimal method for synthesizing multi-bit Toffoli gates in diverse and unpredictable quantum hardware specifications.
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spelling doaj.art-9624d49686c9410594247ae14b2636b52023-03-24T23:00:42ZengIEEEIEEE Access2169-35362023-01-0111273422735110.1109/ACCESS.2023.324379810041026Optimal Multi-Bit Toffoli Gate SynthesisYoung-Min Jun0https://orcid.org/0000-0002-4882-6341In-Chan Choi1https://orcid.org/0000-0002-0068-3564Quantum Machine Learning Laboratory, School of Industrial Management Engineering, Korea University, Seoul, South KoreaQuantum Machine Learning Laboratory, School of Industrial Management Engineering, Korea University, Seoul, South KoreaMulti-bit Toffoli gates form an essential quantum gate class for quantum algorithms. They should be efficiently decomposed into elementary single- or multi-qubit quantum gates, such as CNOT, T, and Hadarmard, for a scalable implementation of a quantum algorithm. We propose an engineering method for the practical synthesis of a multi-bit Toffoli gate. Two optimization models and their closed-form solutions are presented for optimal decomposition of the multi-bit Toffoli gate. These models are based on linearized multi-objective integer programming with parameters such as the number of target ancillae, ancillae states, and basis gates. The proposed method supports the systematic handling of quantum circuit constraints, including the total number of available qubits and maximum circuit depth, which depend on various quantum hardware specifications. Our approach exhibits promise in the noisy intermediate-scale quantum environment by providing a rapid and optimal method for synthesizing multi-bit Toffoli gates in diverse and unpredictable quantum hardware specifications.https://ieeexplore.ieee.org/document/10041026/Combinatorial optimizationNISQquantum algorithmToffoli gate synthesis
spellingShingle Young-Min Jun
In-Chan Choi
Optimal Multi-Bit Toffoli Gate Synthesis
IEEE Access
Combinatorial optimization
NISQ
quantum algorithm
Toffoli gate synthesis
title Optimal Multi-Bit Toffoli Gate Synthesis
title_full Optimal Multi-Bit Toffoli Gate Synthesis
title_fullStr Optimal Multi-Bit Toffoli Gate Synthesis
title_full_unstemmed Optimal Multi-Bit Toffoli Gate Synthesis
title_short Optimal Multi-Bit Toffoli Gate Synthesis
title_sort optimal multi bit toffoli gate synthesis
topic Combinatorial optimization
NISQ
quantum algorithm
Toffoli gate synthesis
url https://ieeexplore.ieee.org/document/10041026/
work_keys_str_mv AT youngminjun optimalmultibittoffoligatesynthesis
AT inchanchoi optimalmultibittoffoligatesynthesis