Proving AX(BXC) = B(A(dot)C) - C(A(dot)B)

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In summary, the conversation discusses the expansion of the right hand side of the equation AX(BXC) = B(A(dot)C) - C(A(dot)B) and the use of summation convention and Levi-Civita tensor to prove the result. Participants also mention the use of cartesian tensors and the three dimensional cross product.
  • #1
starbaj12
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AX(BXC) = B(A(dot)C) - C(A(dot)B)

For the left hand side I got

(AyBxCy-AyByCx+AzBxCz-AzBzCx)x(hat) + (-AxBxCy+AxByCx+AzByCz-AzBzCy)y(hat) + (-AxBxCz+AxBzCx-AyByCz+AyBzCy)z(hat)

Is this right?

Where would I go from here to prove the rest?

Thanks for the help
 
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  • #2
expand the RHS, and see if they were equal
 
  • #3
Learn summation convention as that's how you ought to prove this result, otherwise it's just messy.
 
  • #4
matt grime said:
Learn summation convention as that's how you ought to prove this result, otherwise it's just messy.

Yeah,use cartesian tensors.And Levi-Civita (cartesian) tensor.This is ugly.

:yuck:


Daniel.
 
  • #5
Not sure about the neccesity to learn about tensors as such since I could do this question, with summation convention, well before I knew what a tensor was. Admittedly the things involved are tensors, but there's no need to know this (I mean, we aren't even transforming anything).
 
  • #6
Last edited by a moderator:
  • #7
[tex] \epsilon_{ijk}\epsilon_{lmn}= \left[
\begin{array}{ccc}
\delta_{il} & \delta_{im} & \delta_{in} \\
\delta_{jl} & \delta_{jm} & \delta_{jn} \\
\delta_{kl} & \delta_{km} & \delta_{kn} \\
\end{array}
\right]
[/tex]

is the product of Levi-Civita tensors. Using this and
[tex] \vec{a} \cross \vec{b} = \epsilon_{ijk}a_{i}b_{j} [/tex] and
[tex] \vec{a} \cdot \vec{b} = a_{i}b_{i} [/tex]

you should be able to prove any vector identity. I relearned this technique one week when it was really boring at work a couple of years ago.
 

What is the mathematical equation "Proving AX(BXC) = B(A(dot)C) - C(A(dot)B)"?

The equation "Proving AX(BXC) = B(A(dot)C) - C(A(dot)B)" is a mathematical proof that shows the equality between the product of three matrices (A, B, and C) and the difference between the product of two matrices (A and C) and the product of two matrices (A and B) multiplied by the third matrix (C).

What is the purpose of proving this equation?

The purpose of proving this equation is to demonstrate the validity and consistency of the mathematical operations involved in matrix multiplication. It also helps to establish a deeper understanding of the relationships between matrices and their products.

What are the key concepts involved in proving this equation?

The key concepts involved in proving this equation are the properties of matrix multiplication, such as the associative and distributive properties, as well as the commutative property of scalar multiplication. Additionally, the proof also relies on the properties of transpose and dot product of matrices.

What are some common mistakes made when attempting to prove this equation?

Some common mistakes made when attempting to prove this equation include incorrectly applying the properties of matrix multiplication, not considering the order of operations, and making errors in the arithmetic calculations. It is important to carefully follow each step of the proof and double-check all calculations to avoid these mistakes.

How can this equation be applied in real-world situations?

This equation can be applied in real-world situations involving vector spaces and linear transformations. For example, it can be used in computer graphics to rotate and scale objects, in physics to calculate the forces and motions of particles, and in economics to model supply and demand relationships.

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