SuperEncoder: Towards Efficient Neural Approximate Quantum State Preparation

doi:10.1109/TC.2025.3644034

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	SuperEncoder: Towards Efficient Neural Approximate Quantum State Preparation
	Zhao, Yilun 1,2; Wang, Bingmeng 3; Jiang, Wenle 4; Pan, Xiwei 5; Li, Bing 6; Han, Yinhe 1,2; Wang, Ying 1,2
	2026-03-01
发表期刊	IEEE TRANSACTIONS ON COMPUTERS
ISSN	0018-9340
卷号	75 期号:3 页码:916-927
摘要	Numerous quantum algorithms assume that classical data has already been converted into quantum states, a process known as Quantum State Preparation (QSP). However, achieving precise QSP requires a circuit depth that scales exponentially with the number of qubits, posing a significant challenge to realizing quantum advantage. Recent research explores Parameterized Quantum Circuits (PQCs) as an approximate alternative, offering improved scalability with reduced circuit depth. However, the iterative, state-by-state optimization required by this approach creates substantial runtime overhead, which severely limits its practicality. To improve the efficiency of approximate QSP, we introduce a novel two-stage framework that can potentially generate QSP circuits for arbitrary quantum states. In the offline training stage, our model learns a direct mapping from target states to circuit parameters, thereby bypassing the need for online, state-by-state optimization during the inference stage. Extensive evaluations show that our approach significantly reduces runtime overhead by up to 132x, making a steady step towards efficient neural approximate QSP.
关键词	Quantum state Qubit Training Runtime Optimization Encoding Iterative methods Vectors Quantum circuit Quantum algorithm Quantum state preparation performance optimization
DOI	10.1109/TC.2025.3644034
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Hardware & Architecture ; Engineering, Electrical & Electronic
WOS记录号	WOS:001690579300032
出版者	IEEE COMPUTER SOC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/42792
专题	中国科学院计算技术研究所
通讯作者	Wang, Ying
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100190, Peoples R China 3.Univ Rochester, Rochester, NY 14627 USA 4.ByteDance, Beijing 100098, Peoples R China 5.Hong Kong Univ Sci & Technol, Guangzhou 511453, Peoples R China 6.Chinese Acad Sci, Inst Microelect, Beijing 100029, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Yilun,Wang, Bingmeng,Jiang, Wenle,et al. SuperEncoder: Towards Efficient Neural Approximate Quantum State Preparation[J]. IEEE TRANSACTIONS ON COMPUTERS,2026,75(3):916-927.
APA	Zhao, Yilun.,Wang, Bingmeng.,Jiang, Wenle.,Pan, Xiwei.,Li, Bing.,...&Wang, Ying.(2026).SuperEncoder: Towards Efficient Neural Approximate Quantum State Preparation.IEEE TRANSACTIONS ON COMPUTERS,75(3),916-927.
MLA	Zhao, Yilun,et al."SuperEncoder: Towards Efficient Neural Approximate Quantum State Preparation".IEEE TRANSACTIONS ON COMPUTERS 75.3(2026):916-927.