Finite Element Methods
The finite element method (FEM) provides a systematic framework for approximating PDEs on complex domains. By working with weak formulations and piecewise polynomial spaces, FEM combines mathematical rigor with practical flexibility.
Variational Formulation
Consider the boundary value problem in , on . The weak formulation seeks such that for all , where is the bilinear form and is the linear functional. By the Lax-Milgram theorem, if is continuous and coercive, there exists a unique weak solution.
The Galerkin method restricts the weak formulation to a finite-dimensional subspace : find such that for all . Choosing a basis for and writing leads to the stiffness system where and .
Finite Element Spaces
On a triangulation of , the space of continuous piecewise linear (P1) elements is . The hat functions form a basis: at mesh vertices. The stiffness matrix is sparse (bandwidth in 2D) and SPD for coercive . Higher-order elements (P2, P3, ...) use additional degrees of freedom at edge midpoints or interior nodes.
For on , , with equally spaced interior nodes: the stiffness matrix is and the mass-weighted load vector has entries . The FEM solution equals the FD solution when is evaluated by the trapezoidal rule.
Error Estimates
For P elements with mesh size : and (Aubin-Nitsche trick). The estimate gains one order over the estimate. For P1 elements: in and in . Adaptive mesh refinement uses a posteriori error estimators to locally refine the mesh where the error is large, achieving optimal convergence rates even for singular solutions.