Prove that tensor is second rank mixed

In summary, E^alpha_beta is a mixed second rank tensor because it follows the transformation properties of a second rank mixed tensor and is invariant under coordinate transformations, assuming that V and U are arbitrary vectors.
  • #1
Mcfly11
6
0

Homework Statement



V^alpha and U^beta are both contravariant vectors, and obey the equation V^alpha=E^alpha_beta*U^beta. Show that E^alpha_beta is a mixed second rank tensor. (Note: I couldn't get the latex to work, my apologies for the ugly equations. E^alpha_beta means E with a superscript alpha, and subscript beta.)

Homework Equations


The transformation equation of mixed second rank tensors (kind of a bummer to type without the latex working for me...)

The Attempt at a Solution



The only solution I can come up with assumes that the equation is invariant under coordinate transformation...which doesn't seem valid to me. Basically, I transformed the two vectors V and U into 'barred' coordinates using the standard transformation for contravariant vectors, and substitute that into the equation given...then if the form of the equation is to remain invariant under coordinate transformations, it required that E follows the transformation properties of a second rank mixed tensor. I assume this is altogether invalid due to my assumption of invariance...can anyone offer me a starting point or a tip? Thanks!
 
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  • #2
You reasoning is correct. You need to use two things: invariance (or covariance, if you wish), and arbitrariness of V and U. You did not mention the second condition and it was not explicitly stated in the problem. But evidently if that equation should hold only for, say, U=0, V=0, then you would not be able to say anything reasonable about E,
 

1. What is a tensor?

A tensor is a mathematical object that represents a physical quantity such as force, displacement, or stress. It is characterized by its rank, which is a measure of its degree of complexity.

2. What does it mean for a tensor to be second rank mixed?

Second rank mixed means that the tensor has two indices, one covariant and one contravariant, and each index can take on multiple values. This allows the tensor to represent a quantity that has both directional and positional components.

3. How do you prove that a tensor is second rank mixed?

To prove that a tensor is second rank mixed, you need to show that it satisfies the properties of a second rank mixed tensor. This includes having two indices, being linearly transformable, and obeying the transformation laws for covariant and contravariant indices.

4. What are some examples of second rank mixed tensors?

Examples of second rank mixed tensors include stress, strain, and inertia tensors. These are used in mechanics to describe the stress and strain on a material, as well as the distribution of mass in a system.

5. Why is it important to understand second rank mixed tensors?

Second rank mixed tensors are important in physics and engineering because they allow us to describe complex physical quantities that have both directional and positional components. They are also used in many mathematical applications, such as in differential geometry and general relativity.

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