What books should I read to fill my knowledge gap in tensor analysis?

In summary, Tensor analysis is a branch of mathematics and physics that focuses on studying the properties of tensors, which are geometric objects used to describe relationships between different quantities. It is important because it provides a powerful framework for solving problems in physics and engineering, and has applications in various fields such as relativity, fluid dynamics, and electromagnetism. A strong math background, particularly in linear algebra and multivariate calculus, is needed to understand tensor analysis. Recommended books for learning tensor analysis include "Introduction to Tensor Calculus, Relativity, and Cosmology" by Derek F. Lawden, "Tensor Analysis" by Edward Nelson, and "Tensor Analysis: Theory and Applications" by I. S. Sokolnikoff and R. M
  • #1
Fantini
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I had a badly taught Advanced Linear Algebra course and it covered tensor algebra, resulting in a knowledge gap. What books would you recommend, if any? Exterior algebra, exterior calculus, Clifford and Grassmann algebras included wouldn't be bad ideas as well.
 
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  • #2
Fantini said:
I had a badly taught Advanced Linear Algebra course and it covered tensor algebra, resulting in a knowledge gap. What books would you recommend, if any? Exterior algebra, exterior calculus, Clifford and Grassmann algebras included wouldn't be bad ideas as well.

Hi Fantini,

For a basic idea about tensors I referred, Schaum's Outlines Vector Analysis (And An Introduction to Tensor Analysis) Once I did a General Relativity course and I found A Brief on Tensor Analysis (Undergraduate Texts in Mathematics) quite good, although I didn't read it apart from the first few chapters.
 
  • #3
I'm sorry to hear that you had a bad experience with your Advanced Linear Algebra course. It's definitely frustrating when a course doesn't cover all the necessary material or doesn't teach it well. Here are some books that I would recommend for filling in the knowledge gap and learning about tensor algebra, exterior algebra, exterior calculus, and Clifford and Grassmann algebras:

1. "Tensor Algebra and Tensor Analysis for Engineers" by Mikhail Itskov: This book provides a clear and concise introduction to tensor algebra and tensor analysis, with plenty of examples and exercises to help you practice.

2. "Exterior Algebra" by Peter Lax: This book covers the basics of exterior algebra and its applications in geometry and physics. It's a great resource for understanding the fundamentals of this subject.

3. "A Geometric Approach to Differential Forms" by David Bachman: This book introduces exterior calculus and differential forms in a geometric way, making it easier to understand the concepts and their applications.

4. "Clifford Algebras and Spinors" by Pertti Lounesto: This book provides a thorough introduction to Clifford algebras and their applications in physics and geometry.

5. "Grassmann Algebra: Exploring Extended Vector Space" by John Browne: This book covers the basics of Grassmann algebra and its applications in geometry, physics, and computer science.

I hope these recommendations help you in filling the gaps in your knowledge and expanding your understanding of these important topics. Best of luck in your studies!
 

Related to What books should I read to fill my knowledge gap in tensor analysis?

What is Tensor Analysis?

Tensor analysis is a branch of mathematics and physics used to study the properties of geometric objects called tensors. These objects are used to describe the relationships between different quantities in a space.

Why is Tensor Analysis important?

Tensor analysis is important because it provides a powerful mathematical framework for understanding and solving problems in physics and engineering. It is used in a wide range of fields, including relativity, fluid dynamics, electromagnetism, and mechanics.

What are some common applications of Tensor Analysis?

Some common applications of tensor analysis include studying the properties of materials, analyzing the flow of fluids, and understanding the behavior of electromagnetic fields. It is also used in machine learning and artificial intelligence for data analysis and pattern recognition.

Do I need a strong math background to understand Tensor Analysis?

Yes, tensor analysis requires a strong foundation in mathematics, particularly in linear algebra and multivariate calculus. It also helps to have a basic understanding of physics concepts such as vectors, matrices, and differential equations.

What are some recommended books for learning Tensor Analysis?

Some recommended books for learning tensor analysis include "Introduction to Tensor Calculus, Relativity, and Cosmology" by Derek F. Lawden, "Tensor Analysis" by Edward Nelson, and "Tensor Analysis: Theory and Applications" by I. S. Sokolnikoff and R. M. Redheffer.

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