anchor.diff:  
   #### Divergence of a vector-to-vector function
   
  -Signature: `AD.Div(Func<D[],D[]>)`
  -
  -Return value: `Func<D[],D>`
  -
  -For a function $\mathbf{F}: \mathbb{R}^n \to \mathbb{R}^n$ with components $F_1(a_1, \dots, a_n),\; \dots, \; F_n(a_1, \dots, a_n)$, this gives the [divergence](http://en.wikipedia.org/wiki/Divergence), that is, the trace of the Jacobian matrix
  +Syntax: `public static Func<D[],D> AD.Div(Func<D[],D[]> f)`
  +
  +For a function $\mathbf{F}: \mathbb{R}^n \to \mathbb{R}^n$ with components $F_1(a_1, \dots, a_n),\; \dots, \; F_n(a_1, \dots, a_n)$, this returns a function that computes the [divergence](http://en.wikipedia.org/wiki/Divergence), that is, the trace of the Jacobian matrix
   
   $$$
     \textrm{div} \, \mathbf{F} = \nabla \cdot \mathbf{F} = \textrm{tr}\left( \mathbf{J}_{\mathbf{F}} \right) = \left( \frac{\partial F_1}{\partial a_1} + \dots + \frac{\partial F_n}{\partial a_n}\right) \; .
  
positive.code: 
  #### Curl of a vector-to-vector function
  
  Signature: `AD.Curl(Func<D[],D[]>)`
  
  Return value: `Func<D[],D[]>`
  
  For a function $\mathbf{F}: \mathbb{R}^3 \to \mathbb{R}^3$ with components $F_1(a_1, a_2, a_3),\; F_2(a_1, a_2, a_3),\; F_3(a_1, a_2, a_3)$ this gives the [curl](http://en.wikipedia.org/wiki/Curl_(mathematics)), that is,
  
  $$$
    \textrm{curl} \, \mathbf{F} = \nabla \times \mathbf{F} = \left[ \frac{\partial F_3}{\partial a_2} - \frac{\partial F_2}{\partial a_3}, \; \frac{\partial F_1}{\partial a_3} - \frac{\partial F_3}{\partial a_1}, \; \frac{\partial F_2}{\partial a_1} - \frac{\partial F_1}{\partial a_2} \right] \; .
  
negative.code: 
  #### Transposed Jacobian-vector product
  
  Syntax: `public static D[] AD.JacobianTv(Func<D[],D[]> f, D[] x, D[] v)`
  
  For a function $\mathbf{F}: \mathbb{R}^n \to \mathbb{R}^m$, $\mathbf{x} \in \mathbb{R}^n$, and $\mathbf{v} \in \mathbb{R}^m$, this returns the matrix product of the transposed Jacobian of $\mathbf{F}$ at $\mathbf{x}$ with $\mathbf{v}$
  
  $$$
    \left( \mathbf{J}_\mathbf{F}^\textrm{T} \right)_\mathbf{x} \mathbf{v} \; .
  