【学术视频】第九届量子多体系计算研讨会 | 重庆大学张学锋博士

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图 | 张学锋博士

题   目：Floquet induced superfluidity of two-species hardcore bosons in l-d optical lattice

报告人：张学锋

单   位：重庆大学

时   间：2019-04-20

地   点：中国人民大学

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研究背景

Quantum simulation is a new front hot topic of physics research. As an important quantum simulator, the ultra-cold atoms in the optical lattice system also become a new platform for studying the many-body physics because of its many advantages including fine-tuning property. Especially recently, the technique of periodically tuning based on Floquet theory has been developed rapidly. By periodically driving tunable parameters in the experiment, many exotic interactions are designed including the artificial gauge field, density dependent hopping and so on. It not only extends the range of the quantum simulation, but also provides an ideal platform for studying the quantum many body systems, especially topological phase and phase transition. However, the quantum many body systems is hardly analytically solved, especially when interactions are so strong that the band theory or conventional perturbation theory fails. In numerical side, different methods have their own shortcoming, such as sign problem of quantum Monte Carlo (QMC) or high dimension consideration of density matrix renormalization group (DMRG). Thus, implementing different numerical methods on one problem has become a new trend.

报告提纲

• Floquet engineering a density dependent hopping two-species hard core Bose-Hubbard model.

• A new integrable point is found at  J0 [K] =0 where some hopping processes are totally suppressed.

• The periodical modulation can induce the superfluid phase, but also the exotic gauge dressed superfluid phase with new pairing from and can be mapped to normal superfluid with hidden symmetry transformation.

个人简介

张学锋博士，2006年山西大学物理基地班学士毕业，2011年在中科院理论物理所获得博士学位，之后先后在德国凯泽斯劳腾理工大学，马克斯普朗克复杂系统物理所从事博士后研究。2017年起任职于重庆大学。主要通过量子蒙特卡洛数值模拟方法研究阻挫强关联系统中的新奇量子相，以及相关的拓扑激发与拓扑相变。

会议简介

This workshop will focus on recent advances in the field of quantum many-body computation, including Monte Carlo methods, renormalization group and tensor network methods, machine learning, etc. It aims to provide young researchers and graduate students with introductory and updated research information, promote exchange of ideas and in-depth discussions, and enhance the interactions of researchers working in relevant areas.

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