密度矩阵与张量网络重正化(Density Matrix and Tensor Network Renormalization)

密度矩阵与张量网络重正化(Density Matrix and Tensor Network Renormalization)
作 者: 向涛
出版社: 北京大学出版社
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作者简介

  向涛 中国科学院物理研究所研究员,中国科学院院士、发展中国家科学院院士,北京量子信息科学研究院院长。1984年本科毕业于清华大学,1986年在清华大学获得硕士学位,1990年在中国科学院理论物理研究所获得博士学位。《中国物理快报》主编。从事凝聚态物理,特别是强关联量子问题的理论研究。

内容简介

《Density Matrix and Tensor Network Renormalization(密度矩阵与张量网络重正化)》介绍了过去三十年发展起来的张量网络态重正化群理论。《Density Matrix and Tensor Network Renormalization(密度矩阵与张量网络重正化)》首先介绍了张量网络态的分解和取值所需的张量代数基础。之后,《Density Matrix and Tensor Network Renormalization(密度矩阵与张量网络重正化)》又介绍了量子态的张量网络表示、量子算子、配分函数(例如矩阵乘积态)、投影纠缠对态等。接下来,《Density Matrix and Tensor Network Renormalization(密度矩阵与张量网络重正化)》又介绍了密度矩阵重正化群(DMRG)及其各种拓展,比如动量空间DMRG、经典或量子跃迁矩阵重整化群方法、时间依赖DMRG、动力学DMRG等。《Density Matrix and Tensor Network Renormalization(密度矩阵与张量网络重正化)》适合凝聚态物理,特别是张量网络态领域的科研工作者参考,也可用于初入此研究方向的青年学者学习。

图书目录

Contents

Preface

Unit Used

Notations and Graphical Representations

List of Abbreviations

Introduction

1.1 Quantum Many-Body Problems

1.2 From NRG to DMRG

1.3 From DMRG to Tensor Network Algorithms

1.4 Applications

2 Basic Algebra of Tensors

2.1 Diagrammatic Representation of Tensors

2.2 QR and LQ Decompositions

2.3 LU Decomposition with Partial Pivoting

2.4 Singular Value Decomposition

2.5 Polar Decomposition

2.6 Higher-Order Singular Value Decomposition

2.7 Low-Rank Approximation of Tensors

2.8 Automatic Differentiation

2.9 Trotter-Suzuki Decomposition

3 Tensor Network Representation of Classical Statistical Models

3.1 Tensor Network Models

3.2 Matrix-Network Models

3.3 Tensor Network Representation in the Original Lattice

3.4 Tensor Network Representation in the Dual Space

3.5 Vertex-Sharing Lattice Models

3.6 Duality Properties of Tensor Network Models

4 Tensor Network Representation of Operators

2 Notations and Graphical Representations

4.1 Matrix Product Operators (MPO)

4.2 Imaginary Time Evolution Operato

4.3 Quantum Transfer Matrix

4.4 MPO Representation of Quantum Transfer Matrix

5 Tensor Network Ansatz ofWave Functions

5.1 Area Law of Entanglement Entropy

5.2 Matrix Product States (MPS)

5.3 One-Dimensional AKLT States

5.4 Multiscale Entanglement Renormalization Ansatz (MERA)

5.5 Projected Entangled Pair State (PEPS)

5.6 Projected Entangled Simplex State (PESS)

6 Criterion of Truncation: Symmetric Systems

6.1 Density Matrix

6.2 Reduced Density Matrix

6.3 Schmidt Decomposition

6.4 Variational Approach

6.5 Edge and Bond Density Matrices

7 Real-Space DMRG

7.1 Two Kinds of Algorithms

7.2 DMRG in the MPO Language

7.3 Error Analysis

7.4 Heisenberg Spin Chains

7.5 Periodic System

7.6 Multiple Target States

7.7 Two-Dimensional Systems

8 Implementation of Symmetries

8.1 Symmetry Consideration

8.2 Continuous Abelian Symmetries

8.3 Spin Reflection Symmetry

8.4 Spatial Reflection Symmetry

8.5 Non-Abelian Symmetries

9 DMRG with Nonlocal Basis States

9.1 General Consideration

9.2 Momentum-Space DMRG

9.3 DMRG in a General Basis Space

9.4 Optimization of Single-Particle Basis States

9.5 Optimizing Active Basis Space

Notations and Graphical Representations 3

10 Matrix Product States

10.1 The DMRG Wave Function

10.2 Canonical Representations

10.3 Canonical Transformation

10.4 Implementation of Symmetries

11 Infinite Matrix Product States

11.1 Translation Invariant MPS

11.2 Transfer Matrix and Canonical Transformation

11.3 Expectation Values of Physical Observables

11.4 String Order Parameter

11.5 MPS with a Finite Unit Cell

12 Determination of MPS

12.1 Variational Optimization

12.2 Excited states

12.3 Imaginary Time Evolution

12.4 Purification

13 Continuous Matrix Product States

13.1 Lattice Discretization of Continuous Quantum Field Theory

13.2 Continuum limit of MPS

13.3 Expectation Values

13.4 Canonicalization

13.5 Determination of Continuous MPS

14 Classical Transfer Matrix Renormalization

14.1 Classical Transfer Matrix

14.2 TMRG

14.3 Fixed-Point MPS: One-site Approach

14.4 Fixed-Point MPS: Two-Site Approach

14.5 Corner Transfer Matrix Renormalization

15 Criterion of Truncation: Nonsymmetric Systems

15.1 Nonsymmetric Density Matrix

15.2 Transformation Matrices

15.3 Canonicalization of the Transformation Matrices

15.4 Biorthonormalization

15.5 Low-Rank Approximation to the Environment Density Matrix

16 Renormalization of Quantum Transfer Matrices

16.1 Quantum Transfer Matrix and Thermodynamics

16.2 Correlation Functions

4 Notations and Graphical Representations

16.3 QTMRG

16.4 Thermodynamics of the Heisenberg Spin Chain

17 MPS Solution of QTMRG

17.1 Biorthonormal MPS

17.2 Biorthonormalization

17.3 Fixed-Point Equations

17.4 Translation Invariant System with a Finite Unit Cell

18 Dynamical Correlation Functions

18.1 Spectral Functions

18.2 Continued-Fraction Expansion

18.3 Dynamical Moments

18.4 Lanczos-DMRG Method

18.5 Dynamical Calculations with MPS

18.6 Correction-Vector Method

18.7 Spin Structure Factor of the Heisenberg Model

19 Time-Dependent Methods

19.1 Pace-Keeping DMRG

19.2 Time-Evolving Block Decimation

19.3 Adaptive Time-Dependent DMRG

19.4 Folded Transfer Matrix Method

20 Tangent-Space Approaches

20.1 Tangent Vectors of Uniform MPS

20.2 Time-Dependent Variational Principle

20.3 Single-mode excitations

20.4 Excitations Represented with PEPS

21 Tree Tensor Network States

21.1 Canonical Representation

21.2 Canonicalization

21.3 Husimi lattice

21.4 Determination of Tree Tensor Network State

21.5 Upper Bound of the Correlation Length

21.6 Thermodynamics

22 Two-Dimensional Tensor Network States

22.1 PEPS

22.2 Variational Optimization

22.3 Imaginary Time Evolution

22.4 Tensor Derivatives by Automatic Differentiation

Notations and Graphical Representations 5

22.5 Contraction of Double-Layer Tensor Networks

23 Coarse-Graining Tensor Renormalization

23.1 Coarse-Graining Approaches

23.2 TRG

23.3 Second Renormalized TRG

23.4 Determination of the Environment Tensor

23.5 Tensor Network Renormalization (TNR)

23.6 Loop Tensor Network Renormalization (Loop-TNR)

23.7 HOTRG

23.8 Second Renormalized HOTRG

23.9 Comparison of Different Methods

23.10 Three-Dimensional Classical Models

23.11 Two-Dimensional Quantum Lattice Models

Appendix A Other Numerical Methods

A.1 Power Method

A.2 Lanczos Method

A.3 Conjugate Gradient Method

A.4 Arnoldi Method

A.5 Quantum Monte Carlo Simulation

References

Index