Fixed point theorem
From CFD-Wiki
The fixed point theorem is a useful tool for proving existence of solutions and also for convergence of iterative schemes. In fact the latter is used to prove the former. If the problem is to find the solution of
then we convert it to a problem of finding a fixed point
Statement
Let be a complete metric space with distance and let be contractive, i.e., for some ,
Then there exists a unique fixed point such that
Proof
Choose any and define the sequence by the following iterative scheme
If we can show that the sequence has a unique limit independent of the starting value then we would have proved the existence of the fixed point. The first step is to show that is a Cauchy sequence.
Now using the triangle inequality we get, for
where the last inequality follows because . Now since as we see that
which proves that is a Cauchy sequence. Since is complete, this sequence converges to a unique limit . It is now left to show that the limit is a fixed point.
and since is the limit of the sequence we see that the right hand side goes to zero so that
The uniqueness of the fixed point follows easily. Let and be two fixed points. Then
and since we conclude that
Application to solution of linear system of equations
We will apply the fixed point theorem to show the convergence of Jacobi iterations for the numerical solution of the linear algebraic system
under the condition that the matrix is diagonally dominant. Assuming that the diagonal elements are non-zero, define the diagonal matrix
and rewriting we get
which is now in the form of a fixed point problem with
For measuring the distance between two vectors let us choose the maximum norm
We must show that is a contraction mapping in this norm. Now
so that the j'th component is given by
From this we get
and
Hence the mapping is contractive if
which is just the condition of diagonal dominance of matrix . Hence if the matrix is diagonally dominant then the fixed point theorem assures us that the Jacobi iterations will converge.
Application to Newton-Raphson method
Consider the problem of finding the roots of an equation
If an approximation to the root is already available then the next approximation
is calculated by requiring that
Using Taylors formula and assuming that is differentiable we can approximate the left hand side,
so that the new approximation is given by
This defines the iterative scheme for Newton-Raphson method and the solution if it exists, is the fixed point of
If we assume that
in some neighbourhood of the solution then
Thus condition (*) guarantees that is contractive and the Newton iterations will converge.