Tensor network for spectrum (Jun. 28, 2021)

  • Published: 2021-06-25

Time: 10:00am, Jun. 28 (Mon.), 2021

Venue: KITS 4th Floor Meeting Room, No. 7 Building, UCAS [View Map]


Speaker: Haiyuan Zou (SJTU)



Tensor network is a thriving subject in modern quantum physics, especially in strongly-correlated many-body system. It provides a natural language, which captures the entanglement features, the criticality, the holography, etc., to describe quantum states of matter and represent many lattice field models. In this talk, two applicative examples of advanced tensor network methods will show the power of tensor network to connect with down-to-earth experiments. First, I will present our tensor network spectrum results, which bridge the essential E8 physics in the quantum integrable model and the realistic dynamics in the quasi-one-dimensional antiferromagnetic material. Second, I will present our prediction of a gapless quantum spin liquid state on fractal, by employing a Projected Entangled Simplex States ansatz.


Biography of the speaker: 

Dr. Zou, Haiyuan obtained his B.S from Shandong University in 2008 and Ph. D from the University of Iowa in 2014 with a high energy background. From 2014 to 2017 he was a postdoctoral associate in Pittsburgh University and worked as a visiting scholar in George Mason University occasionally during that time. After 2017, he has joined Tsung-Dao Lee Institute, Shanghai Jiao Tong University as a postdoctoral fellow. His current main research is on strongly-correlated many-body physics, especially the application of state-of-art tensor networks on spin and field models related with magnetic materials and cold-atom dipolar systems. To date, he published journal papers and proceeding on different areas, including five PRL, and others in PRA, PRB, PRD, and PRE, etc.