Deep learning representations for quantum many-body systems on heterogeneous hardware

LiangXiaoLiMingfanXiaoQianChenJunshi

量子计算方向论文：Deep learning representations for quantum many-body systems on heterogen

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内容导读Reading note

分类与摘要Category & abstract

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。

Metadata

完整论文信息Full record

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

Research area

量子计算

Citation

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

BibTeX

@article{acsa2023_44,
  title = {Deep learning representations for quantum many-body systems on heterogeneous hardware},
  year = {2023},
  doi = {10.1088/2632-2153/acc56a}
}