A simple resource about tensors

In summary, the individual is seeking a resource to better understand tensor notation in the context of general relativity. They have found Schutz' First Course In GR to be too advanced and are looking for a simpler alternative. A suggestion is made for Schaums outline on tensor analysis, and another resource titled 'Foundations of Tensor Analysis for Students of Physics and Engineering With an Introduction to the Theory of Relativity' by Joseph C. Kolecki is recommended and can be downloaded from NASA's STI website. The individual expresses appreciation for the suggestion and mentions their previous experience with McConnell's book on tensors.
  • #1
Yhaz
7
0
...is what I am looking for, to understand what is written in GR books.

Schutz' First Course In GR is the simplest I could find which has a part dedicated to their explanation but I am looking for something simpler than that. I am looking for something which is not a long mathematics textbook but explains how to understand what is written in tensor notation.
 
Last edited:
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  • #2
Schaums outline on tensor analysis would be a good place to start. I used mcconnells book when I did an indep study on tensors. It was a Dover publication.
 
  • #3
much appreciated
 
  • #4

Related to A simple resource about tensors

1. What are tensors and what are they used for?

Tensors are mathematical objects that describe the relationship between different quantities or physical properties. They are used to represent and manipulate data in multiple dimensions, making them useful in fields such as physics, engineering, and computer science.

2. How do tensors differ from scalars and vectors?

Tensors differ from scalars (single numbers) and vectors (arrays with magnitude and direction) in that they can have multiple components in different directions. While scalars have 0 components and vectors have 1, tensors can have 2 or more components and can describe complex relationships between multiple quantities.

3. What are some real-world examples of tensors?

Tensors are used in many real-world applications, such as representing forces in mechanics, encoding images in computer vision, and describing the structure of molecules in chemistry. They are also used in machine learning algorithms for tasks like image recognition and natural language processing.

4. What is the difference between a tensor and a matrix?

A matrix is a specific type of tensor with two dimensions, while tensors can have any number of dimensions. Matrices are commonly used to represent linear transformations, while tensors can represent more complex relationships between quantities. Additionally, tensors can have different transformation properties than matrices, such as being invariant under certain rotations.

5. How do I perform operations on tensors?

Operations on tensors, such as addition, multiplication, and differentiation, can be performed using the same rules as for matrices. However, since tensors can have different transformation properties, it is important to pay attention to the order and types of tensors being operated on. Many programming languages also have libraries specifically for performing tensor operations efficiently.

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