MACHINE LEARNING meets QUANTUM PHYSICS

被引：114
作者：
Das Sarma, Sankar [1 ]
Deng, Dong-Ling [2 ]
Duan, Lu-Ming [3 ]
机构：
[1] Univ Maryland, College Pk, MD 20742 USA
[2] Tsinghua Univ, Beijing, Peoples R China
[3] Tsinghua Univ, Inst Interdisciplinary Informat Sci, Beijing, Peoples R China
来源：
PHYSICS TODAY | 2019年 / 72卷 / 03期
关键词：
D O I：
10.1063/PT.3.4164
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
Machine learning is a field of computer science that seeks to build computers capable of discovering meaningful information and making predictions about data. It is the core of artificial intelligence (AI) and has powered many aspects of modern technologies, from face recognition and natural language processing to automated self-driving cars.
引用
收藏
页码：48 / 54
页数：7
相关论文
共 19 条
  • [1] Quantum machine learning
    Biamonte, Jacob
    Wittek, Peter
    Pancotti, Nicola
    Rebentrost, Patrick
    Wiebe, Nathan
    Lloyd, Seth
    [J]. NATURE, 2017, 549 (7671) : 195 - 202
  • [2] Solving the quantum many-body problem with artificial neural networks
    Carleo, Giuseppe
    Troyer, Matthias
    [J]. SCIENCE, 2017, 355 (6325) : 602 - 605
  • [3] Carrasquilla J, 2017, NAT PHYS, V13, P431, DOI [10.1038/nphys4035, 10.1038/NPHYS4035]
  • [4] Quantum machine learning: a classical perspective
    Ciliberto, Carlo
    Herbster, Mark
    Ialongo, Alessandro Davide
    Pontil, Massimiliano
    Rocchetto, Andrea
    Severini, Simone
    Wossnig, Leonard
    [J]. PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2018, 474 (2209):
  • [5] Machine Learning Detection of Bell Nonlocality in Quantum Many-Body Systems
    Deng, Dong-Ling
    [J]. PHYSICAL REVIEW LETTERS, 2018, 120 (24)
  • [6] Machine learning topological states
    Deng, Dong-Ling
    Li, Xiaopeng
    Das Sarma, S.
    [J]. PHYSICAL REVIEW B, 2017, 96 (19)
  • [7] Quantum Entanglement in Neural Network States
    Deng, Dong-Ling
    Li, Xiaopeng
    Das Sarma, S.
    [J]. PHYSICAL REVIEW X, 2017, 7 (02):
  • [8] v Machine learning & artificial intelligence in the quantum domain: a review of recent progress
    Dunjko, Vedran
    Briegel, Hans J.
    [J]. REPORTS ON PROGRESS IN PHYSICS, 2018, 81 (07)
  • [9] A quantum machine learning algorithm based on generative models
    Gao, X.
    Zhang, Z. -Y.
    Duan, L. -M.
    [J]. SCIENCE ADVANCES, 2018, 4 (12):
  • [10] Efficient representation of quantum many-body states with deep neural networks
    Gao, Xun
    Duan, Lu-Ming
    [J]. NATURE COMMUNICATIONS, 2017, 8
12