Tensor multiplication 3 dimesnsions

In summary, by decomposing $A_{ij}$ and $B_{ij}$ into their symmetric and antisymmetric parts, it can be shown that $A_{ij}B_{ij} = (A_{(ij)} + A_{[ij]})(B_{(ij)} + B_{[ij]})$. Additionally, $A_{(ij)}B_{(ij)} + A_{[ij]}B_{[ij]} = \frac{1}{2}(A_{ij}B_{ij} - A_{ji}B_{ji})$, which equals zero, thus proving the original equation.
  • #1
Dustinsfl
2,281
5
\begin{alignat*}{3}
A_{ij}B_{ij} & = & (A_{(ij)} + A_{[ij]})(B_{(ij)} + B_{[ij]})\\
& = & A_{(ij)}B_{(ij)} + A_{(ij)}B_{[ij]} + A_{[ij]}B_{(ij)} + A_{[ij]}B_{[ij]}
\end{alignat*}
$$
A_{(ij)}B_{[ij]} + A_{[ij]}B_{(ij)} = \frac{1}{2}(A_{ji}B_{ij} - A_{ij}B_{ji})
$$
Can I then say $A_{ji}B_{ij} = C_{jj} = C_{3\times 3}$ and $A_{ij}B_{ji} = C_{ii} = C_{3\times 3}$?
Therefore, $A_{(ij)}B_{[ij]} + A_{[ij]}B_{(ij)} = 0$.
 
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  • #2
Dustin, I think you basically solved it in line 1, since
$$
A_{ij} = A_{(ij)} + A_{[ij]}
$$
(decomposition of the tensor into symmetric $(A_{(ij)}$ and antisymmetric $(A_{[ij]})$ parts), so
$$
A_{ij}B_{ij} = (A_{(ij)} + A_{[ij]})(B_{(ij)} + B_{[ij]})
$$

But how does
$$
A_{(ij)}B_{(ij)} + A_{[ij]}B_{[ij]} = (A_{(ij)} + A_{[ij]})(B_{(ij)} + B_{[ij]})
$$
? Thanks
 
  • #3
wmccunes said:
Dustin, I think you basically solved it in line 1, since
$$
A_{ij} = A_{(ij)} + A_{[ij]}
$$
(decomposition of the tensor into symmetric $(A_{(ij)}$ and antisymmetric $(A_{[ij]})$ parts), so
$$
A_{ij}B_{ij} = (A_{(ij)} + A_{[ij]})(B_{(ij)} + B_{[ij]})
$$

But how does
$$
A_{(ij)}B_{(ij)} + A_{[ij]}B_{[ij]} = (A_{(ij)} + A_{[ij]})(B_{(ij)} + B_{[ij]})
$$
? Thanks

If $A_{(ij)}B_{[ij]} + A_{[ij]}B_{(ij)} = 0$ which I am not sure how to show.
 
  • #4
dwsmith said:
If $A_{(ij)}B_{[ij]} + A_{[ij]}B_{(ij)} = 0$ which I am not sure how to show.

Yes nevermind I was looking at your solution backwards. Breaking up $A_{(ij)}B_{[ij]} + A_{[ij]}B_{(ij)}$ into elements it all canceled out except
$$
\frac{1}{2}(A_{ij}B_{ij} - A_{ji}B_{ji})
$$
so if that equals zero we are good...
 
  • #5
wmccunes said:
Yes nevermind I was looking at your solution backwards. Breaking up $A_{(ij)}B_{[ij]} + A_{[ij]}B_{(ij)}$ into elements it all canceled out except
$$
\frac{1}{2}(A_{ij}B_{ij} - A_{ji}B_{ji})
$$
so if that equals zero we are good...

Yup
 

FAQ: Tensor multiplication 3 dimesnsions

What is tensor multiplication in 3 dimensions?

Tensor multiplication in 3 dimensions is a mathematical operation used to combine two or more tensors with three indices each, resulting in a new tensor with six indices. It is commonly used in physics and engineering to represent physical quantities that have both magnitude and direction.

How is tensor multiplication different from regular multiplication?

Tensor multiplication differs from regular multiplication in that it takes into account the direction and orientation of the quantities being multiplied, whereas regular multiplication only considers their magnitude. This allows for more accurate representation of physical quantities in three-dimensional space.

What are some real-world applications of tensor multiplication in 3 dimensions?

Tensor multiplication in 3 dimensions has many applications in physics and engineering, such as in the study of fluid dynamics, elasticity, and electromagnetism. It is also used in computer graphics to represent three-dimensional objects and in data analysis to manipulate and analyze three-dimensional data.

What are the properties of tensor multiplication in 3 dimensions?

The properties of tensor multiplication in 3 dimensions include associativity, distributivity, and commutativity. It also follows the rule of index contraction, where a tensor with two identical indices can be multiplied together to produce a scalar value.

Are there any limitations to tensor multiplication in 3 dimensions?

One limitation of tensor multiplication in 3 dimensions is that it can only be applied to tensors with three indices. Additionally, it may become computationally intensive when dealing with large tensors, making it impractical for certain applications.

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