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
Liang, Xiao; Li, Mingfan; Xiao, Qian; Chen, Junshi; Yang, Chao; An, Hong; He, Lixin, Deep learning representations for quantum many-body systems on heterogeneous hardware, MACHINE LEARNING SCIENCE AND TECHNOLOGY，4（1），2023.3
@article{acsa2023_44,
title = {Deep learning representations for quantum many-body systems on heterogeneous hardware},
year = {2023},
doi = {10.1088/2632-2153/acc56a}
}| title | Deep learning representations for quantum many-body systems on heterogeneous hardware |
|---|---|
| title_zh | 待补充 |
| abstract | 待补充 |
| abstract_zh | 待补充 |
| keywords | AI, Quantum |
| year | 2023 |
| published_date | 待补充 |
| online_date | 待补充 |
| paper_type | Journal |
| publication_status | Published |
| volume | 待补充 |
| issue | 待补充 |
| pages | 待补充 |
| article_number | 待补充 |
| publisher | 4（1） |
| doi | 10.1088/2632-2153/acc56a |
| research_area | 量子计算 |
| tags | AI, Quantum |
| 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 | Liang, Xiao, Li, Mingfan, Xiao, Qian, Chen, Junshi |
| corresponding_authors | 待补充 |
| affiliations | 待补充 |
| funding | 待补充 |