SQAI-NCTS Workshop on Tensor Network and Quantum Embedding

Tensor Network Renormalization and its Applications

26 Mar 2024, 10:00

1h

Room 1220, 2F, Faculty of Science Bldg. 4 (Hongo Campus, The University of Tokyo)

Invited talk Invited talks

Speaker

Tao Xiang (Institute of Physics, Chinese Academy of Sciences)

Description

The tensor-network renormalization group is known for its profound implications for understanding and solving correlated quantum systems. I will explore sophisticated tensor-network techniques for assessing dynamical excitations in low-dimensional quantum lattice models:
1. Introduce a matrix-product representation for low-energy excited states and
present methods for their precise determination. [1]
2. Employ the triangular antiferromagnetic model to investigate the dynamical spectra of two-dimensional quantum lattice modes within the single-mode approximation. [2]
3. Discuss the kicked Ising problem, previously utilized to showcase the benefits of noisy quantum computing through error mitigation on the NISQ quantum computing platform, as a case study for efficiently and accurately calculating the time evolutions of two-dimensional tensor-network states. [3]

[1] X. Li, Z. Zhou, G. Xu, R. Chi, Y. Guo, T. Liu, H. Liao, T. Xiang, Accurate
determination of low-energy eigenspectra with multi-target matrix product states,
Phys. Rev. B 109, 045115 (2024).
[2] R. Chi, Y. Liu, Y. Wan, H. J. Liao, T. Xiang, Spin excitation spectra of anisotropic
spin-1/2 triangular lattice Heisenberg antiferromagnets, Phys. Rev. Lett. 129,
227201 (2022)
[3] H.-J. Liao, K. Wang, Z.-S. Zhou, P. Zhang, T. Xiang, Simulation of IBM's kicked
Ising experiment with Projected Entangled Pair Operator, arXiv:2308.03082