分类与摘要
围绕量子计算实验与系统能力展开，适合作为量子方向的代表性成果入口。
引用
Xuncheng Zhao, Mingfan Li, Qian Xiao, Junshi Chen, Fei Wang, Li Shen, Meijia Zhao, Wenhao Wu, Hong An, Lixin He, Xiao Liang，AI for Quantum Mechanics: High Performance Quantum Many-Body Simulations via Deep Learning，In the Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis，Dallas US, November 13–18, 2022. (CCF A)
@article{acsa2022_60,
title = {AI for Quantum Mechanics: High Performance Quantum Many-Body Simulations via Deep Learning},
year = {2022},
doi = {10.1109/sc41404.2022.00053}
}| title | AI for Quantum Mechanics: High Performance Quantum Many-Body Simulations via Deep Learning |
|---|---|
| title_zh | 待补充 |
| abstract | 待补充 |
| abstract_zh | 待补充 |
| keywords | Quantum, 学位认定 A, CCF A |
| year | 2022 |
| published_date | 待补充 |
| online_date | 待补充 |
| paper_type | Conference |
| publication_status | Published |
| volume | 待补充 |
| issue | 待补充 |
| pages | 待补充 |
| article_number | 待补充 |
| publisher | 待补充 |
| doi | 10.1109/sc41404.2022.00053 |
| research_area | 量子计算 |
| tags | Quantum, 学位认定 A, CCF A |
| category | 量子计算 |
| summary | 围绕量子计算实验与系统能力展开，适合作为量子方向的代表性成果入口。 |
| authors | Xuncheng Zhao, Mingfan Li, Qian Xiao, Junshi Chen, Fei Wang, Li Shen, Meijia Zhao, Wenhao Wu |
| corresponding_authors | 待补充 |
| affiliations | 待补充 |
| funding | 待补充 |