Basic Multivariable Proof Equating Determinant to dot/cross product

In summary, Mark is an undergrad Uni student who is new to these forums. He is trying to equate the determinant of vectors A, B, and C to the dot product of vector A and (vector B cross-product vector C). He is having trouble understanding how to do the calculation and is looking for help. His own approach works, but the calculation ends much earlier than he wants it to. He found help on a FAQ post about how to make the math look pretty.
  • #1
CubicFlunky77
26
0
Hello folks! Just a concise introduction of myself before I get to the task at hand: I'm new to these forums although I have been surfing them frequently for the past 5 years! I am not a math major and quite frankly, my skills in the subject are limited. Be that as it may, my fascination for math has inspired me to pursue a career in either pure math or computational science. My name is Mark and I'm an undergrad Uni student.

K, now on to the task at hand: I am not familiar with symbolic/notation input on these forums so I apologize in advance for my crude way of displaying the question in a pictorial format. Simply put, my goal in the picture is to equate the determinant of vectors A, B and C to the dot product of vector A and (vector B cross-product vector C).

Wow that sounded stupid! Lol, please excuse my naïveté. I have a STRONG feeling I am doing something incorrectly. Can anyone please steer me in the right direction?:

 
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  • #2
Well clearly (using your notation)
$$\mathop{det} ( \vec{A} , \vec{B} , \vec{C} )=\vec{A} \cdot ( \vec{B} \times \vec{C})$$

as there is only one function that has the properties each side has, they must be equal.
This could be shown different ways, but I like.
$$\mathop{det} ( \tau \vec{A} , \tau \vec{B} , \tau \vec{C} )=\mathop{det} ( \vec{A} , \vec{B} , \vec{C} )$$
and
$$\mathop{det} ( \vec{i} , \vec{j} , \vec{k} )=1$$
where $$\tau$$ is any rotation
These properties determine det uniquely
since $$\vec{A} \cdot ( \vec{B} \times \vec{C})$$ has these properties as well the two are equal.
 
  • #3
It looks like you are trying to prove it using the coordinate formula, that (while crude) will work also.
 
  • #4
Well, blimey, that was simple enough! Looks like what I did was overkill:blushing:

Unfortunately, I did not know that [itex]\tau[/itex] stood for rotation.
 
  • #5
Welcome to PF, Mark. Five years is a long to time to lurk without posting.

##\tau## is not a standard notation for rotation. I think R is the most common notation, but I'm not sure if it can be called "standard". Here I guess ##\tau## looks prettier, since you're using uppercase Latin letters for vectors.

Your own approach works, but the calculation ends much earlier. I didn't try to understand everything you did, but here's how I'd do it.
$$
\begin{vmatrix}a_1 & a_2 & a_3\\ b_1 & b_2 & b_3\\ c_1 & c_2 & c_3\\ \end{vmatrix} =a_1\underbrace{\begin{vmatrix}b_2 & b_3\\ c_2 & c_3\end{vmatrix}}_{\displaystyle=(\vec B\times\vec C)_1} -a_2\underbrace{\begin{vmatrix}b_1 & b_3\\ c_1 & c_3\end{vmatrix}}_{\displaystyle=-(\vec B\times\vec C)_2} +a_3\underbrace{\begin{vmatrix}b_1 & b_2\\ c_1 & c_2\end{vmatrix}}_{\displaystyle=(\vec B\times\vec C)_3} =\vec A\cdot(\vec B\times\vec C)
$$
This is the link to the FAQ post about how to make the math look pretty:

https://www.physicsforums.com/showpost.php?p=3977517&postcount=3

If you hit the quote button next to my post, you can see how I did what I did. Same thing with lurflurf's post.
 
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What is a basic multivariable proof equating determinant to dot/cross product?

A basic multivariable proof equating determinant to dot/cross product is a mathematical technique used to show the relationship between the determinant of a square matrix and the dot or cross product of its column vectors.

Why is it important to understand this concept?

Understanding this concept is important because it allows for the simplification and generalization of multivariable proofs, making it easier to solve complex problems in various fields of science and mathematics.

How is determinant related to dot/cross product?

The determinant of a 3x3 matrix is equal to the dot product of the first row with the cross product of the second and third rows. Similarly, the determinant of a 2x2 matrix is equal to the cross product of its column vectors. This relationship can be extended to higher dimensions as well.

What are the applications of this concept?

This concept has various applications in fields such as physics, engineering, and economics. It is used to solve problems involving vectors, linear transformations, and systems of linear equations.

What are some common mistakes made when equating determinant to dot/cross product?

Some common mistakes include confusing the order of the vectors in the dot/cross product, not considering the signs of the vectors in the cross product, and forgetting to account for the dimension of the matrix. It is important to carefully follow the steps of the proof to avoid these errors.

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