I am working through the derivation of the Lagrange-Charpit equations presented in this Wikipedia article: http://en.wikipedia.org/wiki/Method_of_characteristics#Fully_nonlinear_case
I am interested in the "fully" nonlinear case. Where we have:
$$F(x_1,...,x_n,u,p_1,...,p_n)=0 $$ And $$ p_i=\frac{\partial u}{\partial x_i} $$
I am fine with the derivation up until the point where they say that (Also, $\dot{x_i}=dx_i/ds$):
$$\sum_i(\dot{x}_idp_i-\dot{p_i}dx_i)=0 $$
Follows from taking the exterior derivative of:
$$ du-\sum_ip_idx_i=0 $$
From the little I know about exterior derivatives, it seems like doing this would give (for the two dimensional case):
$$0=\left(\frac{\partial p_2}{\partial x_1}-\frac{\partial p_1}{\partial x_2}\right)dx_1\wedge dx_2 $$
Because $ddu=0$ and the anti-symmetry of the wedge product. I don't see how this result leads to the one given. Could someone help me out? I feel like there is something very simple that I am missing.
$ \newcommand{\pd}[2]{ \frac{\partial #1}{\partial #2} } $ Attending to the positive answer to my request from the OP, consider the non-linear 1st order PDE:
$$F(x_i,u,p_i) = 0, \quad i = 1,\ldots, n, \quad p_i = \pd{u}{x_i}, \quad u = u(x_1,\ldots,x_n). \tag{1}$$
Assume $F \in \mathcal{C}^1_{x_i}$ and compute the partial derivative of eq. $(1)$ with respect to $x_i$:
$$\pd{F}{x_i} + \pd{F}{u}\pd{u}{x_i} + \pd{F}{p_i}\pd{p_i}{x_i} = 0,$$
or equivalently:
$$\pd{F}{x_i} + p_i \pd{F}{u} + \pd{F}{p_i}\pd{p_i}{x_i} = 0,$$
which is a quasilinear PDE for $p_i$ which can be readily solved leading the set of equations known as Lagrange-Charpit equations:
where the last equality comes from the fact $\sum_i p_i \mathrm{d}x_i = \mathrm{d}u. $
Hope this helps.
Cheers!