layout | title | name | tags | categories |
---|---|---|---|---|
post |
Dispersion relations for linear systems of PDEs |
Dispersion relations |
wave-equation PDE mathematical-exposition |
labnotebook |
Note: this post was originally written by David Ketcheson.
Fourier analysis is an essential tool for understanding the behavior of solutions to linear equations. Often, this analysis is introduced to students in the context of scalar equations with real coefficients. If nothing more is said, students may mistakenly apply assumptions based on the scalar case to systems, leading to erroneous conclusions. I'm surprised at how often I've seen this, and I've even made the mistake myself.
Students in any undergraduate PDE course learn that solutions of the heat equation
diffuse in time whereas solutions of the wave equation
oscillate in time without growing or decaying. They may even be introduced to a general approach for the Cauchy problem: given an evolution equation
one inserts the Fourier mode solution
to obtain
or simply
The function
- If
is real, then energy is conserved and each mode simply translates. This occurs if only odd-numbered spatial derivatives appear in the evolution equation \eqref{evol}. - If
has negative imaginary part, energy decays in time. The heat equation \eqref{heat} behaves this way. - If
has positive imaginary part, then the energy will grow exponentially in time. This doesn't usually occur in physical systems. An example of this behavior is obtained by changing the sign of the right side in the heat equation to get .
What about the wave equation, which has two time derivatives? Using the same Fourier mode ansatz
\eqref{fourier}, one obtains
$$
\begin{align}
\omega^2 & = k^2
\end{align}
$$
or
In the discussion above, we have assumed that
In practice, we often deal with systems of PDEs or PDEs with complex coefficients, and this intuition is then no longer correct. There is nothing deep or mysterious about this topic, but it's easy to jump to incorrect conclusions if one is not careful. To take a common example, consider the time-dependent Schroedinger equation:
Consider the linear system
$$
\begin{align*}
u_t = A \frac{\partial^j u}{\partial x^j},
\end{align*}
$$
where
In this example, our intuition from the scalar case works: our first-order system, with only odd-numbered derivatives, leads to wave-like behavior. But notice that if
Now that we understand the dispersion relation for systems, it's easy to understand the dispersion relation for the Schrodinger equation. Multiply by
In the most general case, we have systems of linear PDEs with multiple spatial derivatives of different order: $$ \label{gensys} u_t = \sum_{j=0}^n A_j \frac{\partial^j u}{\partial x^j}. $$
Here's a real example from my research. It comes from homogenization of
the wave equation in a spatially varying medium
(see Equation (5.17) of this paper for
more details). It's the wave equation plus some second-derivative terms:
$$
u_t = v_x + v_{xx} \
v_t = u_x - u_{xx}.
$$
You might (if you hadn't read the example above) assume that this system
is dissipative due to the second derivatives.
This system is of the form \eqref{gensys} with
$$
\begin{align}
A_1 & = \begin{pmatrix}
0 & 1 \ 1 & 0
\end{pmatrix}
&
A_2 & = \begin{pmatrix}
0 & 1 \ -1 & 0
\end{pmatrix}.
\end{align}
$$
Of course,
Strictly speaking, Fourier analysis like what we've described can't usually be
applied to \eqref{gensys} because the matrices
Returning to the wave equation, let's consider a different way of writing it as a system: $$ \begin{align*} u_t & = v \ v_t & = u_{xx}. \end{align*} $$ It's easy to check that this system is equivalent to the wave equation -- but notice that it's composed of parts with only even derivatives! (reaction and diffusion equations in the terminology of scalar PDEs). This system is of the form \eqref{gensys} with $$ \begin{align} A_0 & = \begin{pmatrix} 0 & 1 \ 0 & 0 \end{pmatrix} & A_2 & = \begin{pmatrix} 0 & 0 \ 1 & 0 \end{pmatrix}. \end{align} $$ Notice that both eigenvalues of both matrices are equal to zero.