Tensor Analysis and Linear Algebra, what's the difference

In summary, tensor calculus and linear algebra are two different approaches to studying similar subject matter. Tensor calculus is an extension of vector calculus, while linear algebra treats everything as sets and groups of objects acted on by linear functionals in the form of matrices. There is overlap between the two subjects, as tensors are multilinear maps, and knowledge of linear algebra can be applied to the study of tensors in differential geometry.
  • #1
mahinda
13
0
Hi,

I think I have been having this question for some time now. What is the difference between tensor calculus and linear algebra? Both seem to make frequent use of matrices, but they seem to be different subject matter. Can anyone please enlighten me on this issue?
 
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  • #2
mahinda said:
Hi,

I think I have been having this question for some time now. What is the difference between tensor calculus and linear algebra? Both seem to make frequent use of matrices, but they seem to be different subject matter. Can anyone please enlighten me on this issue?

Hi Mahinda,

I'm no expert on either subject, but I've had the same question. I'll attempt to answer it. I think tensor calculus and linear algebra are two different ways of looking at some similar subject matter. Tensor calculus is more like an extension of vector calculus. Calculating derivatives and integrals of multi-variable functions in a more traditional calculus approach.

Linear algbegra takes a less visual, less,geometric approach and treats everything as sets and groups of objects which can be acted on by linear functionals in the form of matrices.

There is definitely overlap in the subject matter.
 
  • #3
There is indeed a lot of overlap, as tensors are multilinear maps.
In linear algebra you study properties of linear maps between vector spaces.
You can then apply your knowledge of linear algebra to your study of tensors, as they are an ordered list of linear maps between many potentially different vector spaces: a multilinear map.
They arise naturally in differential geometry as a generalization of locally linear maps (as derivatives become in vector calculus).
 

1. What is the main difference between tensor analysis and linear algebra?

The main difference between tensor analysis and linear algebra is that tensor analysis deals with multidimensional arrays of numbers (tensors) and their transformations, while linear algebra deals with operations on vectors and matrices.

2. How are tensors and matrices related?

Tensors and matrices are both arrays of numbers, but tensors can have an arbitrary number of dimensions, while matrices are limited to two dimensions. Matrices can be seen as a special case of tensors with only two dimensions.

3. Are tensor analysis and linear algebra used in different fields of science?

While both tensor analysis and linear algebra are used in many fields of science, they are typically used for different purposes. Tensor analysis is commonly used in fields such as physics, engineering, and computer science, while linear algebra is often used in statistics, economics, and other mathematical applications.

4. What are the applications of tensor analysis and linear algebra?

Tensor analysis and linear algebra have a wide range of applications in various fields, including physics, engineering, computer science, statistics, economics, and more. They are used for tasks such as data analysis, image recognition, machine learning, and modeling physical systems.

5. Is knowledge of linear algebra necessary for understanding tensor analysis?

While a basic understanding of linear algebra can be helpful in understanding tensor analysis, it is not necessary. Some concepts in linear algebra, such as matrix multiplication and eigenvectors, may be useful in understanding tensors, but a thorough understanding of linear algebra is not required to learn tensor analysis.

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