Quantum Tensor networks and tensor algebra

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Literature recommendations for tensor networks include "Tensor Networks: From Mathematics to Applications" by Stefan E. Schiefer, which offers a comprehensive overview of tensor networks and relevant mathematical concepts like spectral and singular value decomposition. "An Introduction to Tensor Networks" by M.M. Wolf introduces various aspects of tensor networks along with necessary linear algebra background. G. Vidal's "Quantum Many-Body Systems in Condensed Matter Physics" explores tensor networks in the context of quantum systems and their applications. "Tensor Network Theory" by Guifré Vidal provides an in-depth analysis of tensor networks and related mathematical topics. Finally, "Entanglement in Quantum Information Theory" by John Watrous discusses tensor networks within the framework of quantum information.
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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.
 
By looking around, it seems like Dr. Hassani's books are great for studying "mathematical methods for the physicist/engineer." One is for the beginner physicist [Mathematical Methods: For Students of Physics and Related Fields] and the other is [Mathematical Physics: A Modern Introduction to Its Foundations] for the advanced undergraduate / grad student. I'm a sophomore undergrad and I have taken up the standard calculus sequence (~3sems) and ODEs. I want to self study ahead in mathematics...

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