Optimizing quantum transformation matrices: Block decomposition approach for efficient gate reduction

This paper introduces an algorithm designed to approximate quantum transformation matrix with a restricted number of gates by using the block decomposition technique. Addressing challenges posed by numerous gates in handling large qubit transformations, the algorithm provides a solution by optimizing gate usage while maintaining computational accuracy. Inspired by the block decompose algorithm, our approach processes transformation matrices in a blockwise manner, enabling users to specify the desired gate count for flexibility in resource allocation. Simulations validate the effectiveness of the algorithm in approximating transformations with significantly fewer gates, enhancing quantum computing efficiency for complex calculations.

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Publication Details

Journal
Physical review. A/Physical review, A
Published
2025-04-14
DOI
https://doi.org/10.1103/physreva.111.042613
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00

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article

Optimizing quantum transformation matrices: Block decomposition approach for efficient gate reduction

Xin Wang, Kin Man Lai
Physical review. A/Physical review, A
Quantum Computing Algorithms and Architecture
article

Optimizing quantum transformation matrices: Block decomposition approach for efficient gate reduction

Xin Wang, Kin Man Lai
article en

Abstract

This paper introduces an algorithm designed to approximate quantum transformation matrix with a restricted number of gates by using the block decomposition technique. Addressing challenges posed by numerous gates in handling large qubit transformations, the algorithm provides a solution by optimizing gate usage while maintaining computational accuracy. Inspired by the block decompose algorithm, our approach processes transformation matrices in a blockwise manner, enabling users to specify the desired gate count for flexibility in resource allocation. Simulations validate the effectiveness of the algorithm in approximating transformations with significantly fewer gates, enhancing quantum computing efficiency for complex calculations.

Physical review. A/Physical review, AVol. 111(4)
City University of Hong Kong (HK), City University of Hong Kong, Shenzhen Research Institute (CN), Quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area (CN)
National Natural Science Foundation of China, Shenzhen Fundamental Research Program
Openalex Percentile: Top 97%
Quantum Computing Algorithms and Architecture
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Optimizing quantum transformation matrices: Block decomposition approach for efficient gate reduction — Xin Wang, Kin Man Lai · Physical review. A/Physical review, A (2025) | TGRS Research Map | TGRS