Fast variational quantum algorithms for training neural networks and solving convex optimizations
文献类型：期刊论文
| 作者 | Shao, Changpeng |
| 刊名 | PHYSICAL REVIEW A
 |
| 出版日期 | 2019-04-17 |
| 卷号 | 99期号:4页码:10 |
| ISSN号 | 2469-9926 |
| DOI | 10.1103/PhysRevA.99.042325 |
| 英文摘要 | Variational hybrid quantum classical algorithms to optimizations are important applications for near-term quantum computing. This paper proposes two quantum algorithms (the second one is variational) for training neural networks. Both of them obtain exponential speedup at the number of samples and polynomial speedup at the dimension of the samples over classical training algorithms. Moreover, the proposed quantum algorithms return the classical information of the training weight so that the outputs can be used directly to solve other problems. For practicality, we draw the quantum circuits to implement the two algorithms. Finally, as an inspiration, we show how to apply the variational algorithm to achieve speedup at the number of constraints in solving convex optimization problems. |
| 资助项目 | National Natural Science Foundation of China[11671388] ; CAS Frontier Key Project[QYZDJ-SSW-SYS022] |
| WOS研究方向 | Optics ; Physics |
| 语种 | 英语 |
| WOS记录号 | WOS:000465146100003 |
| 出版者 | AMER PHYSICAL SOC |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/34589]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 通讯作者 | Shao, Changpeng |
| 作者单位 | Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Shao, Changpeng. Fast variational quantum algorithms for training neural networks and solving convex optimizations[J]. PHYSICAL REVIEW A,2019,99(4):10. |
| APA | Shao, Changpeng.(2019).Fast variational quantum algorithms for training neural networks and solving convex optimizations.PHYSICAL REVIEW A,99(4),10. |
| MLA | Shao, Changpeng."Fast variational quantum algorithms for training neural networks and solving convex optimizations".PHYSICAL REVIEW A 99.4(2019):10. |
入库方式： OAI收割
来源：数学与系统科学研究院
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