FieldCondensed Matter
TitleFourth Workshop on Tensor Network States: Algorithms and Applications
Start Date2016-12-12 08:00:00
End Date2016-12-15 18:00:00
PlaceLecture Room A, 4F, 3rd General Building, Nat'l Tsing Hua Univ.
IntroductionTensor network state has emerged as a powerful theoretical tool to study quantum collective phenomena. Various types of tensor network states, such as MPS, MERA, PEPS, and PESS, to name a few, has been used as variational ansatzs to study many-body systems. On the other hand, the tensor network formalism goes beyond numerical methods, and it is also used to classify phases of quantum matter, a computational framework for AdS/CFT correspondence, and even with applications to machine learning.

In this workshop we will bring together experts on tensor network algorithms, and their wide spectrum of applications. We will also devote time in the workshop to explore the application of machine learning techniques to statistical physics, and the relation with the tensor network states. Research talks will be complemented with pedagogical lectures and tutorials.

Invited Speakers:
1. Shuo Yang (Perimeter Institute, Canada)
2. Lei Wang (Chinese Academy of Science, PROC)
3. Kenji Harada (Kyoto University, Japan)
4. Miles Stoudenmire (UC Irvine, USA)
5. Frank Pollmann (MPIPKS, Germany)
6. Ian McCulloch (University of Queensland, Australia)
7. Ruizhen Huang (Chinese Academy of Sciences, PROC)
8. Haijun Liao (Chinese Academy of Sciences, PROC)
9. Guangming Zhang (TsingHua U, PROC)
10. Hiroshi Ueda (RIKEN)
11. Masayuki Ohzeki (Tohoku University)
12. Naoki Kawashima (University of Tokyo)
13. Adil A. Gangat (National Taiwan University)
14. Zhendong Li(Caltech)

International Advisory Committee:
1. Garnet Chen (Caltech)
2. Tomotoshi Nishino (Kobe University)
3. Guifre Vidal (Perimeter Institute)
4. Tao Xiang(IOP, Chinese Academy of Sciences)

Organization Committee:
Ying-Jer Kao
Pochung Chen
Zi-Yuang Xie (Renmin University)
Reference link
Sign-up Date2016-10-12 00:00:00
Sign-up Deadline2016-11-30 17:00:00
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