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IEEE International Conference on Control, Electronics and Computer Technology (ICCECT)

Study on Quantum Phase Transition of 2-D Quantum System by Tensor Network Algorithm

Sheng-Hao Li, Yuanyuan Wu, Fei Xiong

Published Apr 28, 2023• 0 citations
Publisher

Abstract

With the deepening of people's understanding of quantum phase transitions, various efficient numerical algorithms have developed rapidly. It is necessary to develop tensor network algorithms to efficiently generate the ground state wave function of quantum many-body system and then calculate the ground state fidelity per site. This mini review article aims to discusses the tensor network algorithm for studying 2-dimensional quantum lattice systems, namely projected entangled pair state, and introduce how to characterize phase transitions in quantum many-body systems from a novel perspective-fidelity. It includes the wave function updating of projected entangled pair state and the tensor network contraction scheme, which can be used to calculate the ground-state fidelity per site of the quantum system, and the phase diagram of the ground-state can be determined without any knowledge of the order of the 2-dimensional quantum system, thus indicating that tensor network algorithms can provide a means to describe quantum phase transitions.

DOI
10.1109/iccect57938.2023.10141338

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With the deepening of people's understanding of quantum phase transitions, various efficient numerical algorithms have developed rapidly. It is necessary to develop tensor network algorithms to efficiently generate the ground state wave function of quantum many-body system and then calculate the ground state fidelity per site. This mini review article aims to discusses the tensor network algorithm for studying 2-dimensional quantum lattice systems, namely projected entangled pair state, and introduce how to characterize phase transitions in quantum many-body systems from a novel perspective-fidelity. It includes the wave function updating of projected entangled pair state and the tensor network contraction scheme, which can be used to calculate the ground-state fidelity per site of the quantum system, and the phase diagram of the ground-state can be determined without any knowledge of the order of the 2-dimensional quantum system, thus indicating that tensor network algorithms can provide a means to describe quantum phase transitions.
The purpose of this paper is to describe how to describe the phase transition of quantum multibody system from the perspective of the basic concept of quantum information science - fidelity. For systems the traditional way of characterization that undergo a quantum phase transition is Landau's introduction of order and the fluctuation. In particular, for phase transitions caused by spontaneous breaking symmetry, that is, different ground state wave functions are orthogonal to each other. This suggests that, contrary to the ups and downs of traditional expressions, the concept of irrelevant information and vital information can be introduced. By introducing the basic amount of ground lattice fidelity, quantifying irrelevant information and critical information which can identify the quantum phase transition of the system. It is worth emphasizing that no matter the internal order of quantum multibody systems is a traditional symmetry or other novel quantum order, they all can be applied such as topological order, single-grid ground state fidelity. In order to efficiently calculate the single-grid ground state fidelity of quantum multibody systems, tensor network algorithm is needed. This kind of algorithm is the result of the deepening of quantum entanglement in recent years. Quantum entanglement expounds the working principle of real-space renormalization group algorithm, especially density matrix re-grouping algorithm.
The Tensor Network (TN) algorithm for strongly related electronic quantum lattice systems has become the uppermost algorithm for studying strongly related electronic quantum lattice systems in numerical computation. Focusing on the TN algorithm based on 2-D spin systems, this paper discusses the theoretical principles of the Projected Entangled Pair States (PEPS) algorithm and its implementation process. It also explores the infinite PEPS (iPEPS) algorithm for simulating the spin-1/2 infinite 2-D square lattice quantum XYX model. The critical phenomena of the two-dimensional XYX quantum system are analyzed from the perspectives of ground-state fidelity and order parameters, and the quantum critical point is identified. It is anticipated that with the further development of TN algorithms, the single-site fidelity theory of quantum phase transitions (QPTs) can be applied to various quantum many-body systems in condensed matter physics, thereby deepening our understanding of the extremely rich states of matter in the quantum world. Research indicates that quantum information theory provides a universal method for the study of QPTs, which can identify several ground-state fidelities and order parameters through the ground-state wave function of the system, several ground state fidelity and local order parameters can be identified to fully describe some quantum phase transition points, greatly enriching the traditional Landau theory of symmetry breaking QPTs.
We have developed an efficient tensor network algorithm for spin ladders, which generates ground-state wave functions for infinite-size quantum spin ladders. The algorithm is able to efficiently compute the ground-state fidelity per lattice site, a universal phase transition marker, thus offering a powerful tool to unveil quantum many-body physics underlying spin ladders. To illustrate our scheme, we consider the two-leg and three-leg Heisenberg spin ladders with staggering dimerization. The ground-state phase diagram thus yielded is reliable, compared with the previous studies based on the density matrix renormalization group. Our results indicate that the ground-state fidelity per lattice site successfully captures quantum criticalities in spin ladders.
A large class of quantum phase transitions for quantum lattice systems are characterized by local order parameters. It is shown that local order parameters may be systematically constructed from tensor network representations of quantum many-body ground state wave functions by investigating the reduced density matrices for local areas on an infinite-size lattice. Depending on whether or not the system symmetries are spontaneously broken, and whether or not the ground state fidelity per lattice site is continuous, there are four categories of quantum phase transitions for systems with local order parameters. Quantum phase transitions characterized by nonlocal order parameters are discussed, aiming at better understanding quantum systems with topological order.
We have developed an efficient tensor network algorithm for spin ladders, which generates ground-state wave functions for infinite-size quantum spin ladders. The algorithm is able to efficiently compute the ground-state fidelity per lattice site, a universal phase transition marker, thus offering a powerful tool to unveil quantum many-body physics underlying spin ladders. To illustrate our scheme, we consider the two-leg and three-leg Heisenberg spin ladders with staggering dimerization, the two-leg Heisenberg spin ladder with cyclic four-spin exchange, and the ferromagnetic frustrated two-leg ladder. The ground-state phase diagrams thus yielded are reliable, compared with the previous studies based on the the exact diagonalization and the density matrix renormalization group. Our results indicate that the ground-state fidelity per lattice site successfully captures quantum criticalities in spin ladders.
For any D-dimensional quantum lattice system, the fidelity between two ground state many-body wave functions is mapped onto the partition function of a D-dimensional classical statistical vertex lattice model with the same lattice geometry. The fidelity per lattice site, analogous to the free energy per site, is well defined in the thermodynamic limit and can be used to characterize the phase diagram of the model. We explain how to compute the fidelity per site in the context of tensor network algorithms, and demonstrate the approach by analyzing the two-dimensional quantum Ising model with transverse and parallel magnetic fields.