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| Machine Learning for Many-Body Physics |
| 2017-03-07
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| Institute of Theoretical Physics | | Chinese Academy of Sciences | | Key Laboratory of Theoretical Physics | | Seminar | | Title 题目 | Machine Learning for Many-Body Physics | | Speaker 报告人 | 王磊 | | Affiliation 所在单位 | 中科院物理所 | | Date 日期 | 10:30-11:30, Tuesday, Mar.7, 2017 | | Venue 地点 | ITP NEW BULIDING 6420 | | Abstract 摘要 | Machine learning provides us a new toolset and, more importantly, a new way of thinking about many-body physics. I will first give a pedagogical introduction to machine learning, then review its recent applications in many-body physics with personal remarks. Finally, I will talk about our efforts hinge on the question: Can we make new scientific discovery and invent new efficient algorithms with it ? Our answer: YES, hopefully.
Refs:
[1] Lei Wang, 1606.00318
[2] Li Huang and Lei Wang, 1610.02746
[3] Li Huang, Yi-feng Yang and Lei Wang, 1612.01871
| | Contact Person 联系人 | Pan Zhang | |
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