Petrov-Galerkin generalized orthogonality
The key property of the Petrov-Galerkin approach is that the error is in some sense "orthogonal" to the chosen subspaces. Since , we can use as a test vector in the original equation. Subtracting the two, we get the relation for the error, which is the error between the solution of the original problem, , and the solution of the Galerkin equation, , as follows
- for all .
Since the aim of the approximation is producing a linear system of equations, we build its matrix form, which can be used to compute the solution algorithmically.
Let be a basis for and be a basis for . Then, it is sufficient to use these in turn for testing the Galerkin equation, i.e.: find such that
We expand with respect to the solution basis, and insert it into the equation above, to obtain
This previous equation is actually a linear system of equations , where
Symmetry of the matrix
Due to the definition of the matrix entries, the matrix is symmetric if , the bilinear form is symmetric, , , and for all In contrast to the case of Bubnov-Galerkin method, the system matrix is not even square, if