Material Realizations and Novel Properties of Quantum Spin Hall Insulators and Topological Crystalline Insulators
讲座名称：
Material Realizations and Novel Properties of Quantum Spin Hall Insulators and Topological Crystalline Insulators
讲座时间：
2017-09-06
讲座人：
刘军伟
形式：
校区：
兴庆校区
实践学分：
讲座内容：
报告题目:Material Realizations and Novel Properties of Quantum Spin Hall Insulators and Topological Crystalline Insulators
报告人：刘军伟香港科技大学（西交大05级本科）
报告时间：2017年9月6日（周三）上午10：00
报告地点：基础学科大楼B-712会议室
报告摘要:
The last decade has witnessed a remarkable expansion in the understanding of topological states of matter. A quantum state is topological if its ground state wave function bears a distinctive character that can be specified by a topological invariant. While known in both theory and experiment since the 1980s, the recent revolution in topology has been fueled by combination of topology and symmetry, which gives rise to novel states such as topological insulator and topological crystalline insulator. In this talk, I will discuss material realizations and their corresponding novel properties of these symmetry-related topological states and focus on two examples: monolayer WTe2class of quantum spin Hall insulators and PbxSn1-x(Se,Te) class of topological crystalline insulators. Both of these predictions have both been confirmed by several independent experimental groups. The theoretical studies also impulse our discovery of the thinnest ferroelectric materials in SnTe thin films with the experimental group. At last, I will briefly show our newly designed general-purpose numerical method, dubbed self-learning Monte Carlo, which can be 103faster than traditional Monte Carlo method and is very powerful to study the topological states and other interesting properties in strongly correlated systems of large size.
Keywords:
topological insulator, topological crystalline insulator, transition metal chalcogenides, machine learning, Monte Carlo
References:
[1] X. Qian*, J. Liu*, L. Fu, and J. Li，Science346, 1344 (2014)
[2] J. Liu, T. Hsieh, P. Wei, W. Duan, J. Moodera, and L. Fu.Nat. Mater.13, 178-193 (2014)
[3] K. Chang*, J. Liu*, H. Lin, N. Wang, K. Zhao, A. Zhang, F. Jin, Y. Zhong, X. Hu, W. Duan, Q. Zhang, L. Fu, Q. Xue, X. Chen, and S. Ji,Science353, 274-278 (2016)
[4] J. Liu, H. Wang, C. Fang, L. Fu, X. Qian,Nano Lett.17 467-475 (2017)
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