Abstract

We present a compendium of numerical simulation techniques, based on tensor network methods, aiming to address problems of many-body quantum mechanics on a classical computer. The core setting of this anthology are lattice problems in low spatial dimension at finite size, a physical scenario where tensor network methods, both Density Matrix Renormalization Group and beyond, have long proven to be winning strategies. Here we explore in detail the numerical frameworks and methods employed to deal with low-dimensional physical setups, from a computational physics perspective. We focus on symmetries and closed-system simulations in arbitrary boundary conditions, while discussing the numerical data structures and linear algebra manipulation routines involved, which form the core libraries of any tensor network code. At a higher level, we put the spotlight on loop-free network geometries, discussing their advantages, and presenting in detail algorithms to simulate low-energy equilibrium states. Accompanied by discussions of data structures, numerical techniques and performance, this anthology serves as a programmer’s companion, as well as a self-contained introduction and review of the basic and selected advanced concepts in tensor networks, including examples of their applications.

Highlights

  • The understanding of quantum many-body (QMB) mechanics [1] is undoubtedly one of the main scientific targets pursued by modern physics

  • After introducing the concepts and abstract objects which are the building blocks for every tensor network algorithm, we described in detail how these objects are meant to be embedded in a computer

  • We introduced which manipulations, includinglinear algebra routines, are useful for simulation purposes, stressing the interfaces we suggest for the computation in order to be efficient in terms of time and memory usage

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Summary

Introduction

The understanding of quantum many-body (QMB) mechanics [1] is undoubtedly one of the main scientific targets pursued by modern physics. Approaches relying on a semi-classical treatment of the quantum degrees of freedom [11], such as mean field techniques e.g. in the form of the Hartree–Fock method [12], have been applied with various degrees of success. It is well known, that while they are an accurate treatment in high spatial dimensions, they suffer in low dimensions [13], especially in 1D where entanglement and quantum fluctuations are so important that it is not even possible to establish true long-range order through continuous symmetry breaking [14]

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