How do I derive this vector calculus identity?

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Bright Liu
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Homework Statement
As the title says, how can I get this equation?
Relevant Equations
tensor analysis
##(\nabla\times\vec B) \times \vec B=\nabla \cdot (\vec B\vec B -\frac 1 2B^2\mathcal I)-(\nabla \cdot \vec B)\vec B##
##\mathcal I## is the unit tensor
 
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You need to know these.
$$\mathbf a\times(\mathbf b\times\mathbf c)=\mathbf b(\mathbf a\cdot\mathbf c)-\mathbf c(\mathbf a\cdot\mathbf b)$$$$\mathbf a\cdot(\mathbf b\times\mathbf c)=\mathbf b\cdot(\mathbf c\times\mathbf a)=\mathbf c\cdot(\mathbf a\times\mathbf b)$$
 
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Also note that since ##\mathbf{u} \times \mathbf{v} = -\mathbf{v}\times \mathbf{u}##, you have$$\begin{align*}(\mathbf{a} \times \mathbf{b}) \times \mathbf{c} &= - \mathbf{c} \times (\mathbf{a} \times \mathbf{b})\\ \\
&= \mathbf{a} (-\mathbf{c} \cdot \mathbf{b}) - \mathbf{b}(-\mathbf{c} \cdot \mathbf{a}) = -\mathbf{a}(\mathbf{c} \cdot \mathbf{b}) + \mathbf{b}(\mathbf{c} \cdot \mathbf{a})
\end{align*}$$
 
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etotheipi said:
Also note that since ##\mathbf{u} \times \mathbf{v} = -\mathbf{v}\times \mathbf{u}##, you have$$\begin{align*}(\mathbf{a} \times \mathbf{b}) \times \mathbf{c} &= - \mathbf{c} \times (\mathbf{a} \times \mathbf{b})\\ \\
&= \mathbf{a} (-\mathbf{c} \cdot \mathbf{b}) - \mathbf{b}(-\mathbf{c} \cdot \mathbf{a}) = -\mathbf{a}(\mathbf{c} \cdot \mathbf{b}) + \mathbf{b}(\mathbf{c} \cdot \mathbf{a})
\end{align*}$$
Yes, but you cannot do that with a vector operator. ##\nabla\times\vec A## is not ##-\vec A\times\nabla##.
There’s a page of useful looking identities and their derivations at https://en.m.wikipedia.org/wiki/Vector_calculus_identities, but I do not see any that apply easily here.
 
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Bright Liu said:
Homework Statement:: As the title says, how can I get this equation?
Relevant Equations:: tensor analysis

##(\nabla\times\vec B) \times \vec B=\nabla \cdot (\vec B\vec B -\frac 1 2B^2\mathcal I)-(\nabla \cdot \vec B)\vec B##
##\mathcal I## is the unit tensor

Suffix notation is generally the best method (this being a more efficient form of "show that each cartesian component of the left hand side is equal to the corresponding cartesian component of the right hand side").

In particular, [tex] \mathcal{I}_{ij} = \delta_{ij} = \begin{cases} 1 & i = j \\ 0 & i \neq j \end{cases}[/tex] and
[tex] (\mathbf{a} \times \mathbf{b})_i = \epsilon_{ijk}a_jb_k[/tex] where [tex] \epsilon_{ijk} = \begin{cases} 1 & \mbox{$(i,j,k)$ is an even permutation of (1,2,3)} \\<br /> -1 & \mbox{$(i,j,k)$ is an odd permutation of (1,2,3)} \\<br /> 0 & \mbox{otherwise}\end{cases}[/tex] together with the identity [tex] \epsilon_{ijk} \epsilon_{kpq} = \delta_{ip}\delta_{jq} - \delta_{iq}\delta_{jp}[/tex]
 
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haruspex said:
Yes, but you cannot do that with a vector operator. ##\nabla\times\vec A## is not ##-\vec A\times\nabla##.
There’s a page of useful looking identities and their derivations at https://en.m.wikipedia.org/wiki/Vector_calculus_identities, but I do not see any that apply easily here.

Interesting, you're right! My previous, naïve, view was that so long as you work with Cartesian components then it's generally safe to treat ##\nabla \equiv
\begin{pmatrix}
\frac{\partial}{\partial x} & \frac{\partial}{\partial y} & \frac{\partial}{\partial z}
\end{pmatrix}^T##, however you are certainly correct that it doesn't work here, considering that the order of the ##\frac{\partial}{\partial x_i}## and the ##A_j## definitely matters.

In that case, I'll step back and see how yourself and @pasmith approach the problem, for fear of misleading the OP. Working with the components as mentioned in #5 seems like a good idea!
 
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