Tensor networks and tensor algebra

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SUMMARY

This discussion focuses on literature recommendations for understanding tensor networks and their mathematical foundations, specifically highlighting the importance of singular value decomposition and spectral decomposition. Key books recommended include "Tensor Networks: From Mathematics to Applications" by Stefan E. Schiefer, "An Introduction to Tensor Networks: Matrix Product States and Projected Entangled Pair States" by M.M. Wolf, "Quantum Many-Body Systems in Condensed Matter Physics" by G. Vidal, "Tensor Network Theory" by Guifré Vidal, and "Entanglement in Quantum Information Theory" by John Watrous. These resources collectively provide a comprehensive overview of tensor networks and their applications across various fields.

PREREQUISITES
  • Understanding of tensor networks and their applications
  • Familiarity with linear algebra concepts, particularly singular value decomposition
  • Knowledge of spectral decomposition techniques
  • Basic principles of quantum many-body systems in condensed matter physics
NEXT STEPS
  • Study "Tensor Networks: From Mathematics to Applications" by Stefan E. Schiefer for a comprehensive overview
  • Explore "An Introduction to Tensor Networks: Matrix Product States and Projected Entangled Pair States" by M.M. Wolf for foundational concepts
  • Investigate "Quantum Many-Body Systems in Condensed Matter Physics" by G. Vidal to understand applications in physics
  • Read "Tensor Network Theory" by Guifré Vidal for an in-depth analysis of tensor networks
USEFUL FOR

Researchers, physicists, and computer scientists interested in tensor networks, as well as students seeking to strengthen their understanding of linear algebra in the context of quantum information theory.

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I'm looking for literature recommendations regarding tensor networks. I never came across singular value decomposition or spectral decomposition in my linear algebra classes, so I need to brush up on the relevant mathematical background as well.
 
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For literature recommendations regarding tensor networks, consider the following books:1. Tensor Networks: From Mathematics to Applications, by Stefan E. Schiefer. This book provides a comprehensive overview of tensor networks and their applications in physics, computer science, and mathematics. It also covers topics such as spectral decomposition and singular value decomposition. 2. An Introduction to Tensor Networks: Matrix Product States and Projected Entangled Pair States, by M.M. Wolf. This book provides an introduction to various aspects of tensor networks, including their mathematical background. It also discusses the relevant linear algebra topics such as singular value decomposition and spectral decomposition. 3. Quantum Many-Body Systems in Condensed Matter Physics: From Basics to Real-World Applications, by G. Vidal. This book provides a comprehensive overview of quantum many-body systems and their applications in condensed matter physics. It also covers topics such as tensor networks and their applications, as well as relevant linear algebra topics such as singular value decomposition and spectral decomposition. 4. Tensor Network Theory, by Guifré Vidal. This book provides an in-depth look at tensor networks and their applications. It also covers topics such as singular value decomposition and spectral decomposition. 5. Entanglement in Quantum Information Theory, by John Watrous. This book provides an introduction to entanglement in quantum information theory. It also covers topics such as tensor networks and their applications, as well as relevant linear algebra topics such as singular value decomposition and spectral decomposition.
 

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