Is the Divergence of the Cross Product of Gradients Zero?

In summary, the homework equation states that if the derivatives of two vectors are equal, then their cross product is also equal.
  • #1
Payne0511
6
0

Homework Statement


div(grad f x grad g)=0. I need to prove this somehow.


Homework Equations





The Attempt at a Solution



I don't really know where to even start this at >.< any help is greatly appreciated.
 
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  • #2
Write grad(f) and grad(g) out in components and take their cross product. Now take div of that. Use that mixed partial derivatives are equal e.g. d^2(f)/(dxdy)=d^2(f)/(dydx). That will get the job done.
 
  • #3
Personally, I like using index notation for this type of problem; it's a good deal more compact and, once you get used to it, very transparent. Instead of writing out all the components longhand, write [tex] \nabla f \times \nabla g = \tilde{\varepsilon}^{ijk} f_{,i} g_{,j} \hat{\mathbf{e}}_{k} [/tex] , where [tex] \tilde{\varepsilon} [/tex] is the Levi-Civita symbol (not being careful about index placement here, since we're in flat space). Then you have
[tex]
\begin{align*}
\nabla \cdot (\nabla f \times \nabla g) &= \tilde{\varepsilon}^{ijk} (f_{,i} g_{,j})_{,k}\\
&= \tilde{\varepsilon}^{ijk} f_{,i,k} g_{,j} + \tilde{\varepsilon}^{ijk} f_{,i} g_{,j,k} \textrm{.}
\end{align*}
[/tex]
Both summands in the last equation vanish. Indeed, let [tex] P = \tilde{\varepsilon}^{ijk} f_{,i,k} g_{,j} [/tex] . Then, since partials commute, we have [tex] P = \tilde{\varepsilon}^{ijk} f_{,k,i} g_{,j} [/tex] ; by a trivial relabeling of dummy indices, this gives [tex] P = \tilde{\varepsilon}^{kji} f_{,i,k} g_{,j} = -\tilde{\varepsilon}^{ijk} f_{,i,k} g_{,j} = -P [/tex] (since [tex] \tilde{\varepsilon} [/tex] is completely antisymmetric), so [tex] P = 0 [/tex]. The logic for the other summand is identical.
 
  • #4
Alternatively, if you've already proven the following identities in class, you can simply combine them with [itex]\textbf{A}=\mathbf{\nabla}f[/itex] and [itex]\textbf{B}=\mathbf{\nabla}g[/itex] and the result becomes apparent.

Identities:

[tex]\mathbf{\nabla}\cdot(\textbf{A}\times\textbf{B})=\textbf{B}\cdot(\mathbf{\nabla}\times\textbf{A})-\textbf{B}\cdot(\mathbf{\nabla}\times\textbf{B})[/tex]

[tex]\mathbf{\nabla}\times(\mthbf{\nabla}f)=0[/tex]
 

FAQ: Is the Divergence of the Cross Product of Gradients Zero?

What is the divergence of a vector field?

The divergence of a vector field is a measure of the "outwardness" or "flux density" of the field at a given point. It represents the amount of "stuff" (such as fluid, energy, or mass) that is flowing out of or into a particular point in the field.

How is the divergence of a vector field calculated?

The divergence of a vector field is calculated by taking the dot product of the vector field with the del operator (∇) and then taking the partial derivatives of each component of the field with respect to each variable.

What is the divergence identity in vector calculus?

The divergence identity, also known as Gauss's law, states that the flux of a vector field through a closed surface is equal to the volume integral of the divergence of the field over the enclosed volume.

How is the divergence identity used in physics?

The divergence identity is used in physics to calculate the flow of a vector field through a closed surface, such as the flow of electric or magnetic fields through a closed surface in electromagnetism.

What are some real-world applications of the divergence identity?

The divergence identity has many real-world applications, including calculating fluid flow in pipes and channels, analyzing electromagnetic fields in electrical circuits, and modeling the movement of air or water currents in weather patterns.

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