Is the Divergence of the Cross Product of Two Gradients Always Zero?

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In summary, the divergence of the cross product of two gradients is a scalar quantity obtained by taking the dot product of the cross product of two vector fields with the gradient operator. It is only zero if the vector fields are both conservative, and if this is the case, it means that the vector fields have a potential function and are path-independent. The divergence can be calculated using a formula involving the dot product of gradients and curls. It is important in vector calculus and physics as it helps determine if a vector field is conservative and can be represented by a potential function.
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Chris L T521
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Thanks to those who participated in last week's POTW! Here's this week's problem.

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Problem: Let $f,g : \mathbb{R}^3\rightarrow\mathbb{R}$ be differentiable functions. Given that $\mathbf{F}=\langle F_1,F_2,F_3\rangle$ is a differentiable vector field and $\text{div}\,(\mathbf{F})=\nabla\cdot\mathbf{F} = \dfrac{\partial F_1}{\partial x}+\dfrac{\partial F_2}{\partial y}+\dfrac{\partial F_3}{\partial z}$, show that $\text{div}\,(\nabla f\times\nabla g) = 0$.

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This problem was correctly answered by Sudharaka. You can find his solution below.

For any two vector fields, \(\mathbf{F}\mbox{ and }\mathbf{G}\) the following vector identity holds.

\[\text{div}\,(\mathbf{F}\times\mathbf{G}) = \operatorname{curl}(\mathbf{F})\cdot\mathbf{G} \;-\; \mathbf{F} \cdot \operatorname{curl}(\mathbf{G})\]\(\mbox{Replace, }\mathbf{F}\mbox{ by }\nabla f\mbox{ and }\mathbf{G}\mbox{ by }\nabla g\mbox{ and we get, }\)\[\text{div}\,(\mathbf{\nabla f}\times\mathbf{\nabla g}) = \operatorname{curl}(\mathbf{\nabla f})\cdot\mathbf{\nabla g} \;-\; \mathbf{\nabla f} \cdot \operatorname{curl}(\mathbf{\nabla g})\]The curl of the gradient of any scalar field is the zero vector. Therefore, \(\operatorname{curl}(\mathbf{\nabla f})=\mathbf{0}\mbox{ and }\operatorname{curl}(\mathbf{\nabla g})=\mathbf{0}\)\[\therefore\text{div}\,(\mathbf{\nabla f}\times\mathbf{\nabla g}) = 0\]Q.E.D.
 

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

What is the divergence of the cross product of two gradients?

The divergence of the cross product of two gradients refers to the scalar quantity obtained by taking the dot product of the cross product of two vector fields with the gradient operator. It is a measure of the flux of the vector field through an infinitesimal volume element.

Is the divergence of the cross product of two gradients always zero?

In general, no. The divergence of the cross product of two gradients is only zero if the vector fields are both conservative, meaning that their curl is equal to zero. If the vector fields are not conservative, then the divergence of their cross product will not be zero.

What does it mean if the divergence of the cross product of two gradients is zero?

If the divergence of the cross product of two gradients is zero, it means that the vector fields involved are both conservative. This implies that these vector fields represent the gradient of some scalar function, and therefore, they have a potential function. In other words, the vector fields are path-independent, and the work done by these fields is independent of the path taken.

How can the divergence of the cross product of two gradients be calculated?

The divergence of the cross product of two gradients can be calculated using the formula div(cross(A,B)) = dot(grad(A), curl(B)) - dot(grad(B), curl(A)). This involves taking the dot product of one gradient with the curl of the other gradient and subtracting the dot product of the other gradient with the curl of the first gradient.

Why is the divergence of the cross product of two gradients important?

The divergence of the cross product of two gradients is important in vector calculus and physics as it is used to determine if a vector field is conservative. If the divergence is zero, then the vector field can be represented by a potential function, which makes it easier to work with in various mathematical and physical applications.

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