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Question

Math 6610 • Analysis of Numerical Methods I

Spring 2006 • Question 5

Elliptic Equations Consider the standard five-point difference approximation (centered difference for both the gradient and divergence operators) for the variable coefficient Poisson’s equation \[ -\nabla \cdot (a\nabla u)=f \] with Dirichlet boundary conditions, in a two-dimensional rectangular region. We assume that \(a(\mathbf {x})\ge \delta >0\). The approximate solution \(\{u_{i,j}\}\) satisfies a linear system \(Au=b\).

(a) State and prove the maximum principle for the numerical solution \(u_{i,j}\).

(b) Use the maximum principle to show that the coefficient matrix \(A\) is nonsingular.

(c) Derive the matrix \(A\) in the one-dimensional case and show that it is symmetric and positive definite.

(d) With this linear system, do we get convergence with Jacobi iterations? What about Gauss-Seidel iterations? Give reasons for your answers.

Raw LaTeX

{Elliptic Equations} Consider the standard five-point difference
approximation (centered difference for both the gradient and divergence operators)
for the variable coefficient Poisson's equation
\[
  -\nabla\cdot(a\nabla u)=f
\]
with Dirichlet boundary conditions, in a two-dimensional rectangular region. We assume
that \(a(\mathbf{x})\ge \delta>0\). The approximate solution \(\{u_{i,j}\}\) satisfies a
linear system \(Au=b\).

\textbf{(a)} State and prove the maximum principle for the numerical solution
\(u_{i,j}\).

\textbf{(b)} Use the maximum principle to show that the coefficient matrix \(A\) is
nonsingular.

\textbf{(c)} Derive the matrix \(A\) in the one-dimensional case and show that it is
symmetric and positive definite.

\textbf{(d)} With this linear system, do we get convergence with Jacobi iterations?
What about Gauss-Seidel iterations? Give reasons for your answers.