Density Matrix and Tensor Network Renormalization

Renormalization group theory of tensor network states is a powerful tool for studying quantum many-body problems and understanding entangled structures of complex systems. This book provides a pedagogical and comprehensive introduction to the field, with basic statistical and condensed matter physics models used to demonstrate how the tensor network renormalization works. It is ideal for scientists and engineers and as a reference text for a graduate course.

Format: Hardback
Length: 470 pages
Publication date: 31 August 2023
Publisher: Cambridge University Press

Renormalization group theory of tensor networks is a powerful tool for studying quantum many-body problems and provides a new paradigm for understanding entangled structures of complex systems. In recent decades, the theory has rapidly evolved into a universal framework and language employed by researchers in fields ranging from condensed matter theory to machine learning. This book presents a pedagogical and comprehensive introduction to this field for the first time. After an introductory survey on the major advances in tensor network algorithms and their applications, it introduces step-by-step the tensor network representations of quantum states and the tensor-network renormalization group methods developed over the past three decades. Basic statistical and condensed matter physics models are used to demonstrate how the tensor network renormalization works. An accessible primer for scientists and engineers, this book would also be ideal as a reference text for a graduate course in this area.

Renormalization group theory of tensor networks is a powerful tool for studying quantum many-body problems and provides a new paradigm for understanding entangled structures of complex systems. In recent decades, the theory has rapidly evolved into a universal framework and language employed by researchers in fields ranging from condensed matter theory to machine learning. This book presents a pedagogical and comprehensive introduction to this field for the first time. After an introductory survey on the major advances in tensor network algorithms and their applications, it introduces step-by-step the tensor network representations of quantum states and the tensor-network renormalization group methods developed over the past three decades. Basic statistical and condensed matter physics models are used to demonstrate how the tensor network renormalization works. An accessible primer for scientists and engineers, this book would also be ideal as a reference text for a graduate course in this area.

Weight: 1001g
ISBN-13: 9781009398701