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The del operator () is an operator commonly used in vector calculus to find derivatives in higher dimensions. When applied to a function of one independent variable, it yields the derivative. For multidimensional scalar functions, it yields the gradient. If either dotted or crossed with a vector field, it produces divergence or curl, respectively, which are the vector equivalents of differentiation.

\begin{align}
&\nabla=\begin{bmatrix}
\dfrac{\part}{\part x}\\\dfrac{\part}{\part y}\\\dfrac{\part}{\part z}\end{bmatrix}\\
&\text{grad}(f)=\nabla f\\
&\text{div}(\mathbf{F})=\nabla\cdot\mathbf{F}\\
&\text{curl}(\mathbf{F})=\nabla\times\mathbf{F}
\end{align}

There are six ways del can be used to compute second derivatives of multivariable functions.

  • \nabla\cdot\nabla f=\nabla^2f The divergence of the gradient, also know as the Laplacian
  • \nabla\cdot\nabla\mathbf{F}=\nabla^2\mathbf{F} The vector Laplacian, equal to the Laplacian of each component of the vector
  • \nabla\times\nabla f=0 The curl of the gradient, always equal to 0 (see irrotational vector field)
  • \nabla(\nabla\cdot\mathbf{F}) The gradient of the divergence
  • \nabla\cdot(\nabla\times\mathbf{F})=0 The divergence of curl, always equal to 0 (see incompressible vector field)
  • \nabla\times(\nabla\times\mathbf{F})=\nabla(\nabla\cdot\mathbf{F})-\nabla^2\mathbf{F} The curl of the curl

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