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Section 13.2 Classification of PDEs

Subsection 13.2.1 Why do you want to classify solutions?

If we can classify a PDE that we are trying to solve, according to the scheme given below, it will help us extend qualitative knowledge that we have about the nature of solutions of similar PDEs to the current case. Most importantly, the types of initial conditions that are needed to ensure that the solution is unique vary according to the classification–see Section 13.3.

In physics situations, the classification is usually obvious: if there are two time derivatives, the equation is hyperbolic and we will need two initial conditions on the entire spatial region to make the solution unique; if there is only a single time derivative, the equation is parabolic and we will need only a single initial condition; if the equation has no time derivatives, the equation is elliptic and the solutions are qualitatively different from the previous two cases. You should look at the important PDEs in physics listed in Section 13.1 and classify each one.

If you want to see the formal mathematics for the classification (optional), read on:

Subsection 13.2.2 Form of the equation

The most general 2nd order, linear, PDE can be written:

\begin{equation} \LL\psi = b\tag{13.2.1} \end{equation}


\begin{equation} \LL\psi=\sum_{i,j=1}^4 A_{ij}(x_k) {\partial^2\psi\over\partial x_i\partial x_j} +\sum_{i=1}^4 B_i(x_k) {\partial \psi\over\partial x_i} + C(x_k)\psi\tag{13.2.2} \end{equation}

and \(b(x_k)\) is a source term which may depend on the spatial variables \((x_k)\text{.}\)

Subsection 13.2.3 Optional Mathematical Details of the Classification Scheme

The PDE is classified according to the signs of the eigenvalues \(\lambda_i(x_k)\) of the matrix of functions \(A_{ij}(x_k)\text{.}\)

  1. Elliptic: \(\lambda_i(x_k)\) are nowhere vanishing. All have the same sign. Ex: Poisson, Laplace, Helmholtz

    \begin{equation} \nabla^2={\partial^2 ~\over \partial x^2} + {\partial^2 ~\over \partial y^2}+ {\partial^2 ~\over \partial z^2}\tag{13.2.3} \end{equation}
    \begin{equation} A_{ij}=\begin{pmatrix}1\amp 0\amp 0\\0\amp 1\amp 0\\0\amp 0\amp 1 \end{pmatrix}\tag{13.2.4} \end{equation}
  2. Parabolic: One eigenvalue vanishes everywhere (usually time dependence), the others are nowhere vanishing and have the same sign. Ex: Diffusion, Schroedinger

    \begin{equation} A_{ij}=\begin{pmatrix}0\amp 0\amp 0\amp 0\\0\amp 1\amp 0\amp 0\\0\amp 0\amp 1\amp 0\\0\amp 0\amp 0\amp 1 \end{pmatrix}\tag{13.2.5} \end{equation}
  3. Hyperbolic: All eigenvalues are nowhere vanishing. One sign differs from the others. Ex: Wave, Klein-Gordon

    \begin{equation} A_{ij}=\begin{pmatrix}-1\amp 0\amp 0\amp 0\\0\amp 1\amp 0\amp 0\\0\amp 0\amp 1\amp 0\\0\amp 0\amp 0\amp 1 \end{pmatrix}\tag{13.2.6} \end{equation}