Is the Wedge Product of Vectors Equal to the Cross Product?

In summary, the exterior product of two anti-symmetric maps is\omega\wedge\eta = \frac{\Gamma(3)}{\Gamma(2)^2}\operatorname{Alt} (\vec{a} \otimes \vec{b})
  • #1
Mandelbroth
611
24
Consider ##\vec{a}=\begin{bmatrix} a_1 \\ a_2 \\ a_3 \end{bmatrix}## and ##\vec{b}=\begin{bmatrix} b_1 \\ b_2 \\ b_3 \end{bmatrix}##.

Is any part of the following NOT true?

$$\vec{a}\wedge\vec{b}=\frac{1}{2}(\vec{a}\otimes\vec{b}-\vec{b}\otimes\vec{a}) = \frac{1}{2}\begin{bmatrix} 0 & a_1b_2-a_2b_1 & a_1b_3-a_3b_1 \\ a_2b_1-a_1b_2 & 0 & a_2b_3-a_3b_2 \\ a_3b_1-a_1b_3 & a_3b_2-a_2b_3 & 0 \end{bmatrix}$$
(Edited for accuracy to make me feel better :tongue:)

I wasn't sure if that is actually an equality or not. If it is an equality, it makes defining the cross product rather easy. It would just be the Hodge dual of the wedge product of a with b, because the inner product of the cross product of a and b with any basis of the matrix would be 0...
 
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  • #2
##v\wedge w = \frac{1}{2}(v\otimes w - w\otimes v)## by definition i.e. ##(v \wedge w)_{ab} = v_{[a}w_{b]} = \frac{1}{2}(v_{a}w_{b} - v_{b}w_{a})##.
 
  • #3
WannabeNewton said:
##v\wedge w = \frac{1}{2}(v\otimes w - w\otimes v)## by definition i.e. ##(v \wedge w)_{ab} = v_{[a}w_{b]} = \frac{1}{2}(v_{a}w_{b} - v_{b}w_{a})##.
So it's one half of what I put for the second and third parts?
 
  • #4
Mandelbroth said:
So it's one half of what I put for the second and third parts?
If by second and third parts you mean the two expressions following the wedge product (the alternating tensor product and the matrix) then yes.
 
  • #5
WBN has the factor of 2 wrong.

[tex]v \wedge w \equiv v \otimes w - w \otimes v[/tex]
 
  • #6
Ben Niehoff said:
WBN has the factor of 2 wrong.

[tex]v \wedge w \equiv v \otimes w - w \otimes v[/tex]
According to this: http://www.math.stonybrook.edu/~brweber/401s09/coursefiles/Lecture11.pdf page 4
 
  • #7
Ok, based off of one of my texts, ##(v\wedge w)_{ab} = 2v_{[a}w_{b]} = (v\otimes w)_{ab} - (v\otimes w)_{ba}## which makes more sense because then we get that ##^{*}(v\wedge w)_{a} = (v\times w)_{a}## as usual but the notes linked above seem to say otherwise. Where are they getting the half factor from then?
 
  • #8
Either way, the dot product of a basis of the matrix with the cross product is 0, so my direction is going to be fairly clear either way.

WannabeNewton said:
Ok, based off of one of my texts, ##(v\wedge w)_{ab} = 2v_{[a}w_{b]} = (v\otimes w)_{ab} - (v\otimes w)_{ba}## which makes more sense because then we get that ##^{*}(v\wedge w)_{a} = (v\times w)_{a}## as usual but the notes linked above seem to say otherwise. Where are they getting the half factor from then?
I think they forgot something. The second and third parts of the final equality (VERY bottom) are equivalent.

Suppose that ##\omega: V^k \rightarrow K## and ##\eta:V^m\rightarrow K## are two anti-symmetric maps where K is the base field. Then, the exterior product is of the form

$$\omega\wedge\eta = \frac{\Gamma(k+m+1)}{\Gamma(k+1)\Gamma(m+1)}\operatorname{Alt}(\omega \otimes \eta)\implies \vec{a}\wedge\vec{b}=\frac{\Gamma(3)}{\Gamma(2)^2}\operatorname{Alt} (\vec{a} \otimes \vec{b})$$

I could be egregiously wrong, but...
 
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  • #9
It's easiest to think of ##\omega \wedge \eta## as an antisymmetric map. Then for any vector ##X \in V##, ##(\omega \wedge \eta)(X)## is an antisymmetric map ##V^{k+m-1} \to \mathbb{R}## given by

[tex](\omega \wedge \eta)(X) = \omega(X) \wedge \eta + (-1)^k \, \omega \wedge \eta(X)[/tex]
where the notation ##\eta(X)## means that ##X## goes into the first "slot", leaving the remaining ##m-1## slots free.

You'll notice if you follow this idea through, then you don't get the factor of 1/2 that WBN gave.
 
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  • #10
Is this a convention issue? In Lee "Smooth Manifolds", for example, the wedge product is a map ##\wedge :\Lambda ^{k}(V)\times \Lambda ^{l}(V)\rightarrow \Lambda ^{k+l}(V)## defined by ##\eta\wedge \omega = \frac{(k+l)!}{k!l!}\text{Alt}(\eta\otimes \omega)##. So in this case if ##\eta,\omega\in \Lambda ^{1}(V)## then the ##\frac{1}{2}## factor will not appear i.e. we will just get ##\eta\wedge \omega = \eta\otimes \omega-\omega\otimes \eta##. But then why in that pdf, and in this thread: https://www.physicsforums.com/showthread.php?t=150289 do they have factors of ##\frac{1}{2}##?

EDIT: Ok micromass just told me that it's a conventional issue in the definition. There is another convention where the ##\frac{1}{2}## does come in. See page 302 of Lee "Smooth Manifolds".
 
  • #11
Ben Niehoff said:
WBN has the factor of 2 wrong.

[tex]v \wedge w \equiv v \otimes w - w \otimes v[/tex]

His answer isn't wrong. He simply uses a different convention. Many authors use the convention

[tex]\omega\wedge \eta = Alt(\omega \otimes \eta)[/tex]

This is called the determinant convention, for example the paper wbn linked uses it.

Other authors, like Lee, use the Alt convention:

[tex]\omega\wedge \eta = \frac{(k+l)!}{k! l!}Alt(\omega \otimes \eta)[/tex]

I guess it doesn't matter as long as you are consistent.
 
  • #12
I think the confusion comes from the distinction between an n-form and the components of an n-form. Generically, we can write the n-form ##F## as

[tex]F = \frac{1}{n!} F_{a_1 \ldots a_n} \, e^{a_1} \wedge \ldots \wedge e^{a_n}[/tex]
and you'll notice that there is a ##1/n!## here. But this does NOT imply that the components of ##F## are ##\frac{1}{n!} F_{a_1 \ldots a_n}##. Recall the definition of what "components" are, namely

[tex]F_{a_1 \ldots a_n} \equiv F(e_{a_1}, \ldots, e_{a_n})[/tex]
where ##e_i## are the basis of ##V## given by

[tex]e^i (e_j) = \delta^i_j[/tex]
(remember that ##e^i## are a basis of ##V^*##). One could eliminate the ##1/n!## factor above by using the tensor product instead of the wedge product

[tex]F = F_{a_1 \ldots a_n} \, e^{a_1} \otimes \ldots \otimes e^{a_n}[/tex]
assuming, of course, that ##F_{a_1 \ldots a_n}## is antisymmetric.
 
  • #13
micromass said:
His answer isn't wrong. He simply uses a different convention. Many authors use the convention

[tex]\omega\wedge \eta = Alt(\omega \otimes \eta)[/tex]

What is the rule for distributing the interior product over wedge products in this convention? I.e., what is

[tex]i_X (\omega \wedge \eta)[/tex]
 
  • #14
Here's the relevant section in Lee, by the way, if you're interested:
wedge_product.png
 
  • #15
Ben Niehoff said:
What is the rule for distributing the interior product over wedge products in this convention? I.e., what is

[tex]i_X (\omega \wedge \eta)[/tex]

The definitions on both cases seem to differ. In Lee, we have

[tex]i_X\omega(X_1,...,X_{n-1}) = \omega(X,X_1,...,X_{n-1})[/tex]

while in Morita, we have

[tex]i_X\omega(X_1,...,X_{n-1}) = n \omega(X,X_1,...,X_{n-1})[/tex]

I think that this causes that the distribution rule is the same in both cases:

[tex]i_X(\omega\wedge \eta) = i_X(\omega)\wedge \eta + (-1)^n \omega\wedge i_X(\eta)[/tex]
 
  • #16
micromass said:
while in Morita, we have

[tex]i_X\omega(X_1,...,X_{n-1}) = n \omega(X,X_1,...,X_{n-1})[/tex]

How perverse! Mathwonk seems to dislike this ##1/n!## convention as well, he goes on about it for some time in this thread: https://www.physicsforums.com/showthread.php?t=150289
 

What is the wedge product of vectors?

The wedge product, also known as the exterior product, is a mathematical operation that takes two vectors and produces a new vector that is perpendicular to both of the original vectors. It is represented by the symbol ∧ and is commonly used in differential geometry and multilinear algebra.

What is the difference between the wedge product and the dot product?

The dot product, also known as the inner product, is a mathematical operation that takes two vectors and produces a scalar value. It is represented by the symbol · and is commonly used in linear algebra and physics. Unlike the dot product, the wedge product produces a vector rather than a scalar and is used in geometric and topological contexts.

How is the wedge product calculated?

The wedge product is calculated by taking the cross product of two vectors and then multiplying the result by the sine of the angle between the two vectors. This can be represented mathematically as A ∧ B = |A| |B| sin(θ) n, where A and B are the two vectors, θ is the angle between them, and n is the unit vector perpendicular to both A and B.

What are some applications of the wedge product?

One of the most common applications of the wedge product is in differential geometry, where it is used to define the exterior derivative and the Hodge star operator. It is also used in physics, particularly in electromagnetism and relativity, to calculate quantities such as magnetic flux and the curvature of spacetime.

Are there any properties of the wedge product?

Yes, there are several important properties of the wedge product. These include distributivity, associativity, and anticommutativity. The wedge product is also invariant under rotations and reverses sign under reflections. Additionally, the wedge product of two vectors is equal to zero if and only if the vectors are parallel or one of them is zero.

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