Tensor determinant using box product

Good that you got it :tongue:In summary, using index notation and the equations provided, it can be shown that (a) ##\epsilon_{ijk} \det \underline{\bf{A}} = \epsilon_{mnp} A_{mi} A_{nj} A_{pk}## and (b) ##\det \underline{\bf{A}} = \epsilon_{mnp} A_{m1} A_{n2} A_{p3}##. Part (b) can be derived from part (a) by considering the value of ##\epsilon_{123}##.
  • #1
hotvette
Homework Helper
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Homework Statement


Using index notation only (i.e. don't expand any sums) show that:
\begin{align*}
&\text{(a) } \epsilon_{ijk} \det \underline{\bf{A}} = \epsilon_{mnp} A_{mi} A_{nj} A_{pk} \\
& \text{(b) } \det \underline{\bf{A}} = \epsilon_{mnp} A_{m1} A_{n2} A_{p3}
\end{align*}

Homework Equations



\begin{align*}
&\text{(1) }\epsilon_{ijk} \det \underline{\bf{A}} = [\underline{\bf{A}} \underline{e}_i, \underline{\bf{A}} \underline{e}_j, \underline{\bf{A}} \underline{e}_k] \\
& \text{(2) } \underline{\bf{A}} = A_{ij} \underline{e}_i \otimes \underline{e}_j \\
& \text{(3) } \underline{\bf{A}} \underline{e}_j= (A_{pq} \underline{e}_p \otimes \underline{e}_q)\underline{e}_j
= (\underline{e}_q \cdot \underline{e}_j) A_{pq} \underline{e}_p = \delta_{qj} A_{pq} \underline{e}_p = A_{pj} \underline{e}_p
\end{align*}

The Attempt at a Solution


I got part (a) by using (3) for each term of the box product, substituting each of those expressions into the box product, and evaluating.

What baffles me is (b). If I multiply [itex] \epsilon_{ijk} [/itex] times (b) and compare to (a), the net result is:
\begin{align*}
&\epsilon_{mnp} (\epsilon_{ijk} A_{m1} A_{n2} A_{p3}) = \epsilon_{mnp} (A_{mi} A_{nj} A_{pk}) \\
& \epsilon_{ijk} A_{m1} A_{n2} A_{p3} = A_{mi} A_{nj} A_{pk}
\end{align*}

But I have no idea what to do with that (the indices look really goofy). Any tips?
 
Last edited:
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  • #2
hotvette said:
\begin{align*}
&\epsilon_{mnp} (\epsilon_{ijk} A_{m1} A_{n2} A_{p3}) = \epsilon_{mnp} (A_{mi} A_{nj} A_{pk}) \\
& \epsilon_{ijk} A_{m1} A_{n2} A_{p3} = A_{mi} A_{nj} A_{pk}
\end{align*}
You can't go from the first line to the second line by dividing by ##\epsilon_{mnp}## throughout - because there is an summation involved.

To arrive at (b) from (a), consider the value of ##\epsilon_{123}## :wink:
 
  • #3
Ah, thanks. I was applying standard algebra techniques, which I now see is a mistake. Gosh, the answer is soooooo simple! Thanks.

P.S. I'd fiddled with this thing for probably 2 hours. At one point I was on the right track by looking at how to eliminate [itex] \epsilon_{ijk} [/itex] from (a) to isolate the determinant. I thought about multiplying both sides by [itex] \epsilon_{ijk} [/itex] to get [itex] 6 \det(A) = xxx [/itex] but that didn't look promising. Drat!
 
Last edited:
  • #4
Haha, I guess the trick is to realize that the only way you can have explicit labels such as 1,2 and 3 appearing in the indices is by setting them to be so - multiplying by other stuff with arbitrary indices can never give you specific indices.
 

Related to Tensor determinant using box product

What is a tensor determinant?

A tensor determinant is a mathematical concept used to measure the size or volume of a tensor. It is calculated by taking the determinant of a tensor, which is a function that maps a tensor to a scalar value.

How is the tensor determinant calculated?

The tensor determinant is calculated using the box product, also known as the wedge product or exterior product. This involves taking the product of the vectors that make up the tensor and then taking the determinant of the resulting matrix.

Why is the tensor determinant important?

The tensor determinant is important in many areas of mathematics and physics. It is used in calculating the volume of a parallelepiped in multi-dimensional space, and is also used in differential geometry to define the curvature of a space.

What is the relationship between the tensor determinant and the tensor rank?

The tensor determinant is related to the tensor rank in that it is equal to the square root of the determinant of the tensor's Gram matrix, which is a measure of the linear independence of the vectors that make up the tensor. Therefore, the tensor determinant can be used to determine the rank of a tensor.

Can the tensor determinant be negative?

Yes, the tensor determinant can be negative. This occurs when the orientation of the vectors that make up the tensor is flipped, resulting in a negative volume or size measurement. This can be important in certain applications, such as in physics where the sign of the determinant can indicate the direction of a physical quantity.

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