Determinant of 3x3 matrix equal to scalar triple product?

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Discussion Overview

The discussion centers around the relationship between the determinant of a 3x3 matrix and the scalar triple product of its column vectors. Participants explore the mathematical derivation of the determinant and its interpretation in terms of vector operations, specifically focusing on potential errors in notation and calculation.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant asserts that the determinant of a 3x3 matrix can be expressed as the scalar triple product of its column vectors, leading to the equation ##det A = a_1 \cdot (a_2 \times a_3)##.
  • Another participant questions the clarity of notation used in the derivation, particularly the expression ##a_1 e_1 \cdot (a_2 \times a_3)e_1##, suggesting it lacks proper vector structure.
  • A subsequent reply acknowledges the confusion and attempts to clarify the multiplication process involved in calculating the determinant and the cross product.
  • Further discussion highlights the importance of distinguishing between different types of multiplications and suggests that the expression should be reformulated to avoid misinterpretation.
  • One participant proposes using the Levi-Civita symbol to perform the calculations in components as an alternative approach.
  • Another participant confirms that expressing the vectors in terms of their components and applying the triple product is a valid method, noting its equivalence to using the Levi-Civita symbol.

Areas of Agreement / Disagreement

Participants express differing views on the clarity and correctness of the initial derivation. While some agree on the validity of using the scalar triple product, others challenge the notation and approach, indicating that the discussion remains unresolved regarding the best method to demonstrate the relationship.

Contextual Notes

Participants highlight potential limitations in the original notation and calculations, emphasizing the need for careful handling of vector operations and the distinction between scalar and vector products. The discussion does not resolve these issues definitively.

Erithacus
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The determinant of a 3x3 matrix can be interpreted as the volume of a parallellepiped made up by the column vectors (well, could also be the row vectors but here I am using the columns), which is also the scalar triple product.
I want to show that:
##det A \overset{!}{=} a_1 \cdot (a_2 \times a_3 ) ##
with ## A = \begin{pmatrix} a_{11} & a_{12} & a_{13} \\ a_{21} & a_{22} & a_{23} \\ a_{31} & a_{32} & a_{33} \end{pmatrix} ##

I started to develop det A like this:
## det A = a_{11} (a_{22}a_{33}-a_{23}a_{32})-a_{12} (a_{21}a_{33}-a_{23}a_{31})+a_{13} (a_{21}a_{32}-a_{22}a_{31}) ##

With ## e_i ## as unit vectors, this should equal:
## det A = a_1e_1\cdot (a_2 \times a_3)e_1-a_2e_1\cdot (a_1 \times a_3)e_1+a_3e_1\cdot (a_1 \times a_2)e_1 = a_1\cdot (a_2 \times a_3)-a_2\cdot (a_1 \times a_3)+a_3\cdot (a_1 \times a_2) ##

With the rules for cross products I get:
## det A = a_1\cdot (a_2 \times a_3)+a_1\cdot (a_2 \times a_3)+a_1\cdot (a_2 \times a_3) = 3 \cdot a_1 (a_2 \times a_3) ##

Shouldn't I get only ## a_1 (a_2 \times a_3) ##? Not times three. Please, can someone say what I am doing wrong? Or is it right? In that case, how should I interpret it?
 
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Erithacus said:
With ## e_i ## as unit vectors, this should equal:
## det A = a_1e_1\cdot (a_2 \times a_3)e_1-a_2e_1\cdot (a_1 \times a_3)e_1+a_3e_1\cdot (a_1 \times a_2)e_1 = a_1\cdot (a_2 \times a_3)-a_2\cdot (a_1 \times a_3)+a_3\cdot (a_1 \times a_2) ##
Your notation here is not very clear and likely the reason you are not getting the correct result, what do you mean by ##a_1 e_1 \cdot (a_2\times a_3)e_1##? The vector structure here makes no sense.
 
what do you mean by ##a_1 e_1 \cdot (a_2\times a_3)e_1##? The vector structure here makes no sense.

Thank you for answering!
My thought was, that to get ##a_{11}## I could do the multiplication
## a_1 \cdot e_1 = \begin{pmatrix} a_{11} \\ a_{21} \\ a_{31} \end{pmatrix} \cdot \begin{pmatrix} 1 \\ 0 \\ 0 \end{pmatrix} = a_{11} ##

And for the first row in the cross product I do the same thing:
## (a_2\times a_3) \cdot e_1= \begin{pmatrix} a_{12} \\ a_{22} \\ a_{32} \end{pmatrix} \times \begin{pmatrix} a_{13} \\ a_{23} \\ a_{33} \end{pmatrix}\cdot \begin{pmatrix} 1 \\ 0 \\ 0 \end{pmatrix} = a_{22}a_{33}-a_{23}a_{32}##

Or doesn't it work like that?
 
Last edited:
Erithacus said:
Or doesn't it work like that?
It does, but you must be careful because you are mixing different types of multiplications. The quantity you call ##a_1e_1 \cdot (a_2 \times a_3)e_1## should really be ##(a_1\cdot e_1)((a_2\times a_3)\cdot e_1)## and is not a triple vector product. It is the product of two numbers.
 
The quantity you call ##a_1e_1 \cdot (a_2 \times a_3)e_1## should really be ##(a_1\cdot e_1)((a_2\times a_3)\cdot e_1)## and is not a triple vector product.
Okay, I see. Can I get around that or do I have to use a completely different approach to show what I want to show? Could I use the Levi-Civita symbol and do it all in components?
 
You can write ##\vec a_i = a_{i1} \vec e_1 + a_{i2}\vec e_2 + a_{i3}\vec e_3## and just perform the triple product. Of course, this is equivalent to doing it in components using the Levi-Civita symbol.
 

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