Is the Divergence of the Cross Product of Gradients Zero?

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Homework Help Overview

The problem involves proving that the divergence of the cross product of the gradients of two functions is zero, specifically expressed as div(grad f x grad g) = 0. This falls within the subject area of vector calculus and involves concepts related to gradients, divergences, and cross products.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • The original poster expresses uncertainty about how to begin the proof. Some participants suggest writing the gradients in component form and applying the equality of mixed partial derivatives. Others propose using index notation for a more compact representation and explore the implications of the Levi-Civita symbol in the context of the problem.

Discussion Status

Participants are exploring different methods to approach the proof, including component-wise analysis and index notation. There is no explicit consensus yet, but several lines of reasoning are being discussed, indicating a productive exploration of the topic.

Contextual Notes

Some participants reference identities related to the divergence and curl of vector fields, suggesting that prior knowledge from class may be relevant to the discussion. The original poster's request for help indicates a potential gap in understanding these concepts.

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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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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.
 
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*}<br /> \nabla \cdot (\nabla f \times \nabla g) &= \tilde{\varepsilon}^{ijk} (f_{,i} g_{,j})_{,k}\\<br /> &= \tilde{\varepsilon}^{ijk} f_{,i,k} g_{,j} + \tilde{\varepsilon}^{ijk} f_{,i} g_{,j,k} \textrm{.}<br /> \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.
 
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]
 

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