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| Machine Learning for Many-Body Physics |
| 2017-03-07
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Institute of Theoretical Physics |
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Chinese Academy of Sciences |
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Key Laboratory of Theoretical Physics |
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Seminar |
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Title
题目 |
Machine Learning for Many-Body Physics |
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Speaker
报告人 |
王磊 |
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Affiliation
所在单位 |
中科院物理所 |
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Date
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10:30-11:30, Tuesday, Mar.7, 2017 |
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Venue
地点 |
ITP NEW BULIDING 6420 |
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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
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Contact Person
联系人 |
Pan Zhang | |
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