Can tensors be equal in all coordinate systems?

In summary, the homework statement is attempting to prove that if components of any tensor of any rank vanish in one particular coordinate system they vanish in all coordinate systems. The task is to show that if tensor T is equal to tensor W, T_{ij} = W_{ij} in all coordinate systems.
  • #1
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Homework Statement


Task 1. Show that if components of any tensor of any rank vanish in one particular coordinate system they vanish in all coordinate systems.

Task 2. The components of tensor T are equal to the corresponding components of tensor W in one particular coordinate system; that is, [tex]T^0_{ij} = W^0_{ij}[/tex].
Show that tensor T is equal to tensor W, [tex]T_{ij} = W_{ij}[/tex] in all coordinate systems.


Homework Equations





The Attempt at a Solution


task 1. I have no idea how to start
task 2. transforming to the any other coordinate system I obtain:

[tex]T_{i'j'} = A_{i'}^i A_{j'}^j T^0_{ij} = A_{i'}^i A_{j'}^j W^0_{ij} = W_{i'j'}[/tex] is it ok?
 
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  • #2
If you can do 2 you can do 1 by taking [itex]W_{ij}= 0[/itex]]!

But it is easiest to prove 2 by proving 1 first:
You apparently know that if [itex]T^0_{ij}[/itex] are the components of T in one coordinate system, then the coordinates [itex]T_{i'j'}[/itex] in any coordinates system are given by [itex]T_{i'j'}= A^i_{i'}A^j_{j'}T^0_{ij}[/itex]. Okay what if all components of [itex]T^0_{ij}[/itex] are 0?

And if [itex]T^0_{ij}= W^0_{ij}[/tex], then [itex]T^0_{ij}- W^0_{ij}[/itex] is also a tensor, with all components 0.
 
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  • #3
Well the fact from the 1st task is for me intuitive but I don't understand it's formal proof. Because when some components of [tex]T_{ij}[/tex] are 0 (but not all) than the [tex]T_{i'j'}[/tex] can have no 0 components. So why when all components of [tex]T_{ij}[/tex] are 0 then [tex]T_{i'j'}[/tex] are 0 as well? Is it because changing coordinate system is a linear transformation and so 'A(0)=0'?
 
  • #4
Am I right?
 
  • #5
stress is an example of a tensor...If we have a bar (cuboid with a length much greater than other dimensions), and we apply axial forces to it, then there are only normal stresses...however, if we now cut off a piece from it diagonally, then on the inclined surface so obtained, we have both normal and shear stresses...so the same thing appears different in two different perspectives...is this also a basic property of tensors??
 
  • #6
Please help!
 

1. What is a tensor?

A tensor is a mathematical object that describes the relationship between different coordinate systems. It is a generalization of vectors and matrices, and is commonly used in fields such as physics, engineering, and computer science.

2. What are the basic properties of tensors?

The basic properties of tensors include linearity, transformation, and symmetry. Linearity means that scaling or adding tensors together does not change their fundamental properties. Transformation refers to how tensors behave under coordinate transformations. Symmetry refers to the properties of a tensor being the same under certain transformations.

3. How are tensors represented?

Tensors can be represented in various ways, including as arrays of numbers, as mathematical equations, or using index notation. The most common representation is using index notation, where each index represents the direction or component of the tensor.

4. What is the difference between a covariant and contravariant tensor?

A covariant tensor transforms in the same way as the coordinate system, while a contravariant tensor transforms in the opposite way to the coordinate system. In other words, a covariant tensor's components change when the coordinate system changes, while a contravariant tensor's components remain the same.

5. How are tensors used in real-world applications?

Tensors have numerous practical applications, including in physics for describing the laws of motion, in engineering for analyzing stress and strain in materials, and in machine learning for data analysis and pattern recognition. They are also used in computer graphics and image processing for manipulating and transforming digital images.

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