Optimal tree tensor network operators for tensor network simulations: Applications to open quantum systems

Author:

Li Weitang12ORCID,Ren Jiajun3ORCID,Yang Hengrui4ORCID,Wang Haobin5ORCID,Shuai Zhigang14ORCID

Affiliation:

1. School of Science and Engineering, The Chinese University of Hong Kong 1 , Shenzhen 518172, People’s Republic of China

2. Tencent Quantum Lab, Tencent 2 , Shenzhen 518057, People’s Republic of China

3. MOE Key Laboratory of Theoretical and Computational Photochemistry, College of Chemistry, Beijing Normal University 3 , Beijing 100875, People’s Republic of China

4. MOE Key Laboratory of Organic OptoElectronics and Molecular Engineering, Department of Chemistry, Tsinghua University 4 , 100084 Beijing, People’s Republic of China

5. Department of Chemistry, University of Colorado Denver 5 , Denver, Colorado 80217-3364, USA

Abstract

Tree tensor network states (TTNS) decompose the system wavefunction to the product of low-rank tensors based on the tree topology, serving as the foundation of the multi-layer multi-configuration time-dependent Hartree method. In this work, we present an algorithm that automatically constructs the optimal and exact tree tensor network operators (TTNO) for any sum-of-product symbolic quantum operator. The construction is based on the minimum vertex cover of a bipartite graph. With the optimal TTNO, we simulate open quantum systems, such as spin relaxation dynamics in the spin-boson model and charge transport in molecular junctions. In these simulations, the environment is treated as discrete modes and its wavefunction is evolved on equal footing with the system. We employ the Cole–Davidson spectral density to model the glassy phonon environment and incorporate temperature effects via thermo-field dynamics. Our results show that the computational cost scales linearly with the number of discretized modes, demonstrating the efficiency of our approach.

Funder

National Natural Science Foundation of China

China Association for Science and Technology

Guangdong Provincial Natural Science Foundation

Shenzhen City Pengcheng Peacock Talent Program

Publisher

AIP Publishing

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