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.
 
The book is fascinating. If your education includes a typical math degree curriculum, with Lebesgue integration, functional analysis, etc, it teaches QFT with only a passing acquaintance of ordinary QM you would get at HS. However, I would read Lenny Susskind's book on QM first. Purchased a copy straight away, but it will not arrive until the end of December; however, Scribd has a PDF I am now studying. The first part introduces distribution theory (and other related concepts), which...
I've gone through the Standard turbulence textbooks such as Pope's Turbulent Flows and Wilcox' Turbulent modelling for CFD which mostly Covers RANS and the closure models. I want to jump more into DNS but most of the work i've been able to come across is too "practical" and not much explanation of the theory behind it. I wonder if there is a book that takes a theoretical approach to Turbulence starting from the full Navier Stokes Equations and developing from there, instead of jumping from...

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