Eigenvalues and eigenvectors of the second derivative


Explicit formulas for eigenvalues and eigenvectors of the second derivative with different boundary conditions are provided both for the continuous and discrete cases. In the discrete case, the standard central difference approximation of the second derivative is used on a uniform grid.
These formulas are used to derive the expressions for eigenfunctions of Laplacian in case of separation of variables, as well as to find eigenvalues and eigenvectors of multidimensional discrete Laplacian on a regular grid, which is presented as a Kronecker sum of discrete Laplacians in one-dimension.

The continuous case

The index j represents the jth eigenvalue or eigenvector and runs from 1 to. Assuming the equation is defined on the domain, the following are the eigenvalues and normalized eigenvectors. The eigenvalues are ordered in descending order.

Pure Dirichlet boundary conditions

Pure Neumann boundary conditions

Periodic boundary conditions

.

Mixed Dirichlet-Neumann boundary conditions

Mixed Neumann-Dirichlet boundary conditions

The discrete case

Notation: The index j represents the jth eigenvalue or eigenvector. The index i represents the ith component of an eigenvector. Both i and j go from 1 to n, where the matrix is size n x n. Eigenvectors are normalized. The eigenvalues are ordered in descending order.

Pure Dirichlet boundary conditions

Pure Neumann boundary conditions

Periodic boundary conditions

Mixed Dirichlet-Neumann boundary conditions

Mixed Neumann-Dirichlet boundary conditions

Derivation of Eigenvalues and Eigenvectors in the Discrete Case

Dirichlet case

In the 1D discrete case with Dirichlet boundary conditions, we are solving
Rearranging terms, we get
Now let. Also, assuming, we can scale eigenvectors by any nonzero scalar, so scale so that.
Then we find the recurrence
Considering as an indeterminate,
where is the kth Chebyshev polynomial of the 2nd kind.
Since, we get that
It is clear that the eigenvalues of our problem will be the zeros of the nth Chebyshev polynomial of the second kind, with the relation.
These zeros are well known and are:
Plugging these into the formula for,
And using a trig formula to simplify, we find

Neumann case

In the Neumann case, we are solving
In the standard discretization, we introduce and and define
The boundary conditions are then equivalent to
If we make a change of variables,
we can derive the following:
with being the boundary conditions.
This is precisely the Dirichlet formula with interior grid points and grid spacing. Similar to what we saw in the above, assuming, we get
This gives us eigenvalues and there are. If we drop the assumption that, we find there is also a solution with and this corresponds to eigenvalue.
Relabeling the indices in the formula above and combining with the zero eigenvalue, we obtain,

Dirichlet-Neumann Case

For the Dirichlet-Neumann case, we are solving
where
We need to introduce auxiliary variables
Consider the recurrence
Also, we know and assuming, we can scale so that
We can also write
Taking the correct combination of these three equations, we can obtain
And thus our new recurrence will solve our eigenvalue problem when
Solving for we get
Our new recurrence gives
where again is the kth Chebyshev polynomial of the 2nd kind.
And combining with our Neumann boundary condition, we have
A well-known formula relates the Chebyshev polynomials of the first kind,, to those of the second kind by
Thus our eigenvalues solve
The zeros of this polynomial are also known to be
And thus
Note that there are 2n + 1 of these values, but only the first n + 1 are unique. The th value gives us the zero vector as an eigenvector with eigenvalue 0, which is trivial. This can be seen by returning to the original recurrence. So we consider only the first n of these values to be the n eigenvalues of the Dirichlet - Neumann problem.