【大学频道】北京大学量子材料科学中心呈献 | 北京大学张亿博士

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题   目：Machine Learning for Quantum Materials and Algorithms

报告人：张亿单   位：北京大学时   间：2019-09-25地   点：北京大学

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报告摘要

Today, we face major scientific challenges because the large-scale data acquired by our automated scientific instrumentation and algorithm and the vast degrees of freedom of our target subjects are constantly defying human analysis. Here we sketch concepts, strengths as well as shortcomings of machine learning techniques, and how they may serve as useful tools in overcoming data largeness and noises as well as bridging fields such as between computation and theory, experiment and theory, and even inter-discipline. We report developments in machine learning approaches in recognizing different types of topological phases from quantum many-body states and validating hypothesized order hidden through complex, experimentally-derived electronic quantum matter images at the atomic scale. In particular, we bridge quantum states and classical machine learning techniques coherently with an ensemble of chosen operators we dub as quantum loop topography. We also repeatedly discover a very specific, lattice-commensurate, unidirectional, and translational-symmetry-breaking state favoring particle-like strong-coupling theories of electronic liquid crystals from a large, experimentally-derived electronic quantum matter image archive spanning a wide range of electron densities and energies in carrier-doped cuprates. As a pedagogical example, we outline our progress in using machine learning for efficient and generic quantum computation realizations of quantum adiabatic algorithm and topological quasiparticle braiding.

个人简介

Dr. Zhang, Yi is a theorist in condensed matter physics, focusing on emergent phenomena and novel approaches in quantum materials and systems. He obtained his Ph.D. degree at UC Berkeley. Then he moved to Stanford University as a SITP postdoctoral fellow and later to Cornell University as a Bethe fellow. In 2019, he joined the faculty of International Center for Quantum Materials and the School of Physics at Peking University. Yi Zhang is interested in various quantum algorithm applications including machine learning and quantum entanglement in quantum systems, theoretical characterizations and experimental properties of topological phases and materials, and various other topics. He has published more than 30 papers, including Nature, Nature Physics, PRL, Nature communications, Nano Lett. and others, with citation of over 2000 times.

—— ——往期精彩回顾—— ——● 北京大学量子材料科学中心呈献 | 中国人民大学刘正鑫教授：Quantum Spin Liquid Phases in Extended Kitaev Model● 北京大学量子材料科学中心呈献 | 普林斯顿大学张骏祎：Dipolar Dimer Liquid● 北京大学量子材料科学中心呈献 | 东京大学龚宗平博士：Topological phases of non-Hermitian systems● 北京大学量子材料科学中心呈献 | Yonglong Xie of Princeton University: Visualizing topological and correlated phases with a scanning tunneling microscope● 北京大学量子材料科学中心呈献 | 犹他大学黄华卿研究员：Theoretically Tracing Topological States: from crystals to quasicrystals and to noncrystalline systems● 北京大学量子材料科学中心呈献 | Hengyun Zhou of Harvard University：Surpassing the Interaction Limit to Quantum Metrology with Fault-Tolerant Control● 北京大学量子材料科学中心呈献 | Gang Cao：Control of Quantum States in 4d/5d Transition Metal Oxides● 北京大学量子材料科学中心呈献 | Patrick Rinke：The Artist: Artificial Intelligence for Spectroscopy
● 北京大学量子材料科学中心呈献 | 佛罗里达大学张晓光教授：Multi-phonon processes in solids from first-principles● 北京大学量子材料科学中心呈献 | 中国科学技术大学翟晓芳研究员：Complex oxide thin films and heterostructures for novel physics and applications

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