What Does an Isotropic Cartesian Tensor Look Like in Higher Dimensions?

In summary, a rank-4 isotropic tensor must remain identical under any rotation. However, in principle the derivation for higher ranks can be derived in a similar way. There must be a more powerful approach to finding out.
  • #1
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Does anyone have a proof of what a isotropic cartesian tensor should look like in three or four dimensions?
 
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  • #2
An isotropic tensor must remain identical under any rotation:

t' = R.t.R-1 = t

For three dimensions, for a rotation around the first axis this leads to:

[tex]
\text{t'}(1,1)=t(1,1) \\
\text{t'}(1,2)=t(1,2) \cos (\alpha )-t(1,3) \sin (\alpha ) \\
\text{t'}(1,3)=t(1,2) \sin (\alpha )+t(1,3) \cos (\alpha ) \\
\text{t'}(2,1)=t(2,1) \cos (\alpha )-t(3,1) \sin (\alpha ) \\
\text{t'}(2,2)=t(3,3) \sin ^2(\alpha )+t(2,2) \cos ^2(\alpha )-(t(2,3)+t(3,2)) \sin (\alpha ) \cos (\alpha ) \\
\text{t'}(2,3)=-t(3,2) \sin ^2(\alpha )+t(2,3) \cos ^2(\alpha )+(t(2,2)-t(3,3)) \sin (\alpha ) \cos (\alpha ) \\
\text{t'}(3,1)=t(2,1) \sin (\alpha )+t(3,1) \cos (\alpha ) \\
\text{t'}(3,2)=-t(2,3) \sin ^2(\alpha )+t(3,2) \cos ^2(\alpha )+(t(2,2)-t(3,3)) \sin (\alpha ) \cos (\alpha ) \\
\text{t'}(3,3)=t(2,2) \sin ^2(\alpha )+t(3,3) \cos ^2(\alpha )+(t(2,3)+t(3,2)) \sin (\alpha ) \cos (\alpha ) \\[/tex]
The isotropy condition then leads you to a bunch of relations:

t(1,2) = 0
t(1,3) = 0
t(3,1) = 0
t(2,1) = 0
t(2,2) = t(3,3)
t(2,3) = 0
t(3,2) = 0

The rotations around another axis yields only one additional conclusion:

t(1,1) = t(2,2)
 
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  • #3
I must apologize.
What I meant is rank 3 and rank 4, and not 3rd and 4th dimension. So sorry.
You have got a proof for the general form of rank 3 or rank 4 isotropic cartesian tensor?
 
  • #5
No proof provided :(
 
  • #6
For the permutation symbol, it should be similar to the rank-2 derivation above, just a bit longer.
See: http://mathworld.wolfram.com/PermutationSymbol.html .

For rank-4, there are 3 types of solutions:
"The number of isotropic tensors of rank 0, 1, 2, ... are 1, 0, 1, 1, 3, 6, 15, 36, 91, 232, ... (Sloane's A005043). These numbers are called the Motzkin sum numbers and are given by the recurrence relation ..."
See: http://mathworld.wolfram.com/IsotropicTensor.html

I have no idea what these 3 independent solutions would be.
However, in principles the derivation should go along the sames lines.

I have no idea how the recurrence relation for higher ranks can be derived.
It must be interesting to find out, because it is unlikely that it would be based on the same elementary reasoning.
There must be a more powerful approach.

See also p87and p88 in
 
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FAQ: What Does an Isotropic Cartesian Tensor Look Like in Higher Dimensions?

What are isotropic Cartesian tensors?

Isotropic Cartesian tensors are mathematical objects used in physics and engineering to describe the properties of materials and physical systems. They are tensors that are invariant under rotations and reflections in Cartesian coordinates, meaning they have the same values in all directions.

How are isotropic Cartesian tensors represented?

Isotropic Cartesian tensors are typically represented as matrices or arrays of numbers. The size of the matrix depends on the number of dimensions of the system being described. For example, a 3-dimensional isotropic Cartesian tensor would be represented as a 3x3 matrix.

What are the properties of isotropic Cartesian tensors?

Isotropic Cartesian tensors have several important properties, including being symmetric, traceless, and having a diagonal form. They also have the property of isotropy, meaning they have the same values in all directions.

How are isotropic Cartesian tensors used in physics?

Isotropic Cartesian tensors are used to describe the properties of materials and physical systems in physics, such as elastic moduli, stress and strain, and electric fields. They are also used in the study of fluid mechanics and electromagnetism.

What is the significance of isotropic Cartesian tensors?

Isotropic Cartesian tensors are significant because they simplify the mathematical description of physical systems by reducing the number of variables needed to represent them. They also have important physical implications, such as the relationship between stress and strain in a material.

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