What are some useful vector calculus identities for vector fields A and B?

In summary, the homework statement is that for arbitrary vector fields A and B show that:-∇.(A ∧ B) = B.(∇∧A) - A.(∇∧B)-The Attempt at a Solution
  • #1
hhhmortal
176
0

Homework Statement



For arbitrary vector fields A and B show that:


∇.(A ∧ B) = B.(∇∧A) - A.(∇∧B)





The Attempt at a Solution



I considered only the 'i'-axis, by saying that it is perpendicular with A and B and then I expanded both the left and right side out. The working is too much to post here..I didn't manage to prove it. I was hoping someone would know if there's a useful webpage where I can find out more about vector calculus identities.

Thanks!
 
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  • #2
You can use the fact that

[tex][\mathbf A \times \mathbf B]_i = \epsilon_{ijk} A_j B_k[/tex]

Where there is a summation over repeated indices and [tex]\epsilon_{ijk}[/tex] is completely antisymmetric under an exchange of indices (Levi-Civita symol). That way it's not difficult to prove. Don't know about web sites though.
 
  • #3
Yea, although I'm being asked to prove it without using suffix notation..which is much more tedious
 
  • #4
It is, but it's still a straightforward calculation, just remember the Leibniz rule and keep track of the indices.
 
  • #5
Ok I completed the identity without using suffix notation, but now I will to use it:

My working out is the following:

I take the ith component of both sides, I first start with the left side:[tex]\epsilon[/tex]ijk δ/δx[tex]_{}i[/tex](A_j B_k)And then for the right side:

(B_i ε_ijk δA_k/δx[tex]_{}j[/tex]) - (A_i ε_ijk δB_k/δx[tex]_{}j[/tex])

As you can see the differentials are different, for the left side it is w.r.t the 'i' component while for the right side it is w.r.t 'j' component
 
Last edited:
  • #6
There are no components on either side, the expression is a scalar since it's a dot product. There is a summation over i,j and k so the left hand side is

[tex]\nabla \cdot (\mathbf A \times \mathbf B) = \sum_{i=1}^3 \partial_i (\mathbf A \times \mathbf B)_i = \sum_{i=1}^3 \partial_i (\sum_{j,k=1}^3\epsilon_{ijk} A_j B_k) = \sum_{i,j,k=1}^3 \epsilon_{ijk} \partial_i (A_j B_k)[/tex]

Calculate the derivative and rearrange the terms to get the expression on the right hand side (Hint: use the fact that epsilon is antisymmetric under an exchange of indices).
 
  • #7
phsopher said:
There are no components on either side, the expression is a scalar since it's a dot product. There is a summation over i,j and k so the left hand side is

[tex]\nabla \cdot (\mathbf A \times \mathbf B) = \sum_{i=1}^3 \partial_i (\mathbf A \times \mathbf B)_i = \sum_{i=1}^3 \partial_i (\sum_{j,k=1}^3\epsilon_{ijk} A_j B_k) = \sum_{i,j,k=1}^3 \epsilon_{ijk} \partial_i (A_j B_k)[/tex]

Calculate the derivative and rearrange the terms to get the expression on the right hand side (Hint: use the fact that epsilon is antisymmetric under an exchange of indices).

Oh ok! why is k=1 though? I am a bit confused. So you have summed the left side over i, will this mean :

(A_j )(B_z) will be differentiated w.r.t to dx_i and then I can use the product rule.
 
  • #8
No, the summation is over all three indices, it has to be because the end result is a scalar so there can't be any indices remaining.What the above means is that i goes from 1 to 3, j goes from 1 to 3 and k goes from 1 to 3.

In any case, yes, differentiate w.r.t dx_i inside the sum and you will get two terms. Rearrange them using the antisymmetricity of epsilon and you will get the two terms of the right hand side.
 

1. What is a vector calculus identity?

A vector calculus identity is an equation that relates different vector operations, such as dot product, cross product, and gradient, to each other. These identities are useful in solving problems in vector calculus and can help simplify complex calculations.

2. How many vector calculus identities are there?

There are numerous vector calculus identities, but some of the most commonly used ones include the vector triple product, the vector product identity, and the Lagrange's identity. The exact number of identities may vary depending on the source and context.

3. What is the purpose of vector calculus identities?

The main purpose of vector calculus identities is to simplify and manipulate vector equations. They can also be used to prove other mathematical theorems and solve problems in physics and engineering.

4. Can vector calculus identities be applied to any type of vector?

Yes, vector calculus identities can be applied to any type of vector, including both two-dimensional and three-dimensional vectors. They can also be applied to vectors in different coordinate systems, such as Cartesian, polar, or cylindrical coordinates.

5. How important are vector calculus identities in real-world applications?

Vector calculus identities are essential in many real-world applications, particularly in fields such as physics, engineering, and computer graphics. They are used to solve problems related to motion, forces, and fields, and are also crucial in the development of mathematical models and simulations.

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