Quantum Gate Pattern Recognition and Circuit Optimization for Scientific Applications
There is no unique way to encode a quantum algorithm into a quantum circuit. With limited qubit counts, connectivities, and coherence times, circuit optimization is essential to make the best use of quantum devices produced over a next decade. We introduce two separate ideas for circuit optimization...
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2021-01-01
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doaj-4c5acc7d34344ea588ca5049d19104c72021-08-26T09:27:32ZengEDP SciencesEPJ Web of Conferences2100-014X2021-01-012510302310.1051/epjconf/202125103023epjconf_chep2021_03023Quantum Gate Pattern Recognition and Circuit Optimization for Scientific ApplicationsJang Wonho0Terashi Koji1Saito Masahiko2Bauer Christian W.3Nachman Benjamin4Iiyama Yutaro5Kishimoto Tomoe6Okubo Ryunosuke7Sawada Ryu8Tanaka Junichi9Department of Physics, The University of TokyoInternational Center for Elementary Particle Physics (ICEPP), The University of TokyoInternational Center for Elementary Particle Physics (ICEPP), The University of TokyoPhysics Division, Lawrence Berkeley National LaboratoryPhysics Division, Lawrence Berkeley National LaboratoryInternational Center for Elementary Particle Physics (ICEPP), The University of TokyoInternational Center for Elementary Particle Physics (ICEPP), The University of TokyoDepartment of Physics, The University of TokyoInternational Center for Elementary Particle Physics (ICEPP), The University of TokyoInternational Center for Elementary Particle Physics (ICEPP), The University of TokyoThere is no unique way to encode a quantum algorithm into a quantum circuit. With limited qubit counts, connectivities, and coherence times, circuit optimization is essential to make the best use of quantum devices produced over a next decade. We introduce two separate ideas for circuit optimization and combine them in a multi-tiered quantum circuit optimization protocol called AQCEL. The first ingredient is a technique to recognize repeated patterns of quantum gates, opening up the possibility of future hardware optimization. The second ingredient is an approach to reduce circuit complexity by identifying zero- or low-amplitude computational basis states and redundant gates. As a demonstration, AQCEL is deployed on an iterative and effcient quantum algorithm designed to model final state radiation in high energy physics. For this algorithm, our optimization scheme brings a significant reduction in the gate count without losing any accuracy compared to the original circuit. Additionally, we have investigated whether this can be demonstrated on a quantum computer using polynomial resources. Our technique is generic and can be useful for a wide variety of quantum algorithms.https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_03023.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jang Wonho Terashi Koji Saito Masahiko Bauer Christian W. Nachman Benjamin Iiyama Yutaro Kishimoto Tomoe Okubo Ryunosuke Sawada Ryu Tanaka Junichi |
spellingShingle |
Jang Wonho Terashi Koji Saito Masahiko Bauer Christian W. Nachman Benjamin Iiyama Yutaro Kishimoto Tomoe Okubo Ryunosuke Sawada Ryu Tanaka Junichi Quantum Gate Pattern Recognition and Circuit Optimization for Scientific Applications EPJ Web of Conferences |
author_facet |
Jang Wonho Terashi Koji Saito Masahiko Bauer Christian W. Nachman Benjamin Iiyama Yutaro Kishimoto Tomoe Okubo Ryunosuke Sawada Ryu Tanaka Junichi |
author_sort |
Jang Wonho |
title |
Quantum Gate Pattern Recognition and Circuit Optimization for Scientific Applications |
title_short |
Quantum Gate Pattern Recognition and Circuit Optimization for Scientific Applications |
title_full |
Quantum Gate Pattern Recognition and Circuit Optimization for Scientific Applications |
title_fullStr |
Quantum Gate Pattern Recognition and Circuit Optimization for Scientific Applications |
title_full_unstemmed |
Quantum Gate Pattern Recognition and Circuit Optimization for Scientific Applications |
title_sort |
quantum gate pattern recognition and circuit optimization for scientific applications |
publisher |
EDP Sciences |
series |
EPJ Web of Conferences |
issn |
2100-014X |
publishDate |
2021-01-01 |
description |
There is no unique way to encode a quantum algorithm into a quantum circuit. With limited qubit counts, connectivities, and coherence times, circuit optimization is essential to make the best use of quantum devices produced over a next decade. We introduce two separate ideas for circuit optimization and combine them in a multi-tiered quantum circuit optimization protocol called AQCEL. The first ingredient is a technique to recognize repeated patterns of quantum gates, opening up the possibility of future hardware optimization. The second ingredient is an approach to reduce circuit complexity by identifying zero- or low-amplitude computational basis states and redundant gates. As a demonstration, AQCEL is deployed on an iterative and effcient quantum algorithm designed to model final state radiation in high energy physics. For this algorithm, our optimization scheme brings a significant reduction in the gate count without losing any accuracy compared to the original circuit. Additionally, we have investigated whether this can be demonstrated on a quantum computer using polynomial resources. Our technique is generic and can be useful for a wide variety of quantum algorithms. |
url |
https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_03023.pdf |
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