Consider on a rectangle, with prescribed Dirichlet boundary conditions, and assume initially that the solution is smooth up to the boundary. A finite difference method chooses grid values as unknowns, approximates the differential operator by a local stencil, incorporates the boundary data, and solves the resulting sparse linear system. Accuracy of a stencil by itself is insufficient: one also needs a well-posed discrete problem, a stability estimate uniform under refinement, and a sufficiently accurate algebraic solve.
For a square grid of spacing , centered second differences give the five-point LaplacianExpanding each opposite pair in a Taylor series givesThus the standard equation has second-order normalized local truncation error. Known boundary values move to the right-hand side; they are not iterated as independent unknowns. Nonrectangular geometry requires a consistent boundary approximation rather than silently retaining a full interior stencil outside the domain.
The negative interior operator has positive diagonal and nonpositive off-diagonal entries. For a grid vector extended by zero on the boundary,The edge sum includes links to the fixed boundary. Connectivity makes the matrix positive definite, proving uniqueness and providing an energy structure. The same sign pattern gives a discrete maximum principle: at a negative interior minimum, is nonpositive. If and the boundary is nonnegative, equality can only persist by propagating that minimum through all neighbors to the boundary, a contradiction. Therefore .
On the unit square, the barrier satisfies exactly. If has zero boundary values and , apply the maximum principle to to obtainThe bound is independent of , so the consistency error gives an nodal error. It also separates the algebraic residual from the discretization error: solving the linear system much less accurately than would spoil the spatial accuracy.
A direct higher-order design is possible. In one coordinate,has fourth-order accuracy. Adding the corresponding formula in the other coordinate gives a wider stencil. Its advantages must be balanced against boundary closures, more distant couplings, and the possible loss of monotonicity. Higher order does not automatically imply a stable or geometrically convenient scheme.
The Mehrstellen method takes a different route: it uses the Poisson equation to eliminate leading truncation derivatives while keeping a compact unknown stencil. Define the nine-point finite-difference stencilHere each sum has four terms. Equivalently . Expanding givesThe uncorrected nine-point operator is only second order for a general function. But implies . Moving this known leading defect to the source and approximating its Laplacian with givesIndeed , and multiplication by makes that replacement's error fourth order. In explicit compact form the right-hand side is . Only known source samples, not additional distant solution unknowns, enter this correction. The corresponding unscaled stencil residual is . If , the leading term already vanishes, which explains harmonic superconvergence of the nine-point stencil.
For zero boundary data, has axial link weights and diagonal link weights . Their energy sum proves positive definiteness, and their sign pattern again proves the discrete maximum principle. The same quadratic barrier is exact for , soFor smooth solutions and accurately imposed boundary values this proves fourth-order nodal convergence of the corrected scheme. Singular corners, rough sources or low-order boundary treatment can reduce the observed rate; a formal interior expansion is not a global regularity theorem.
More generally, compact high-order schemes choose a solution stencil and a source stencil together, match their Taylor expansions, and use differentiated forms of the PDE to remove derivatives that would otherwise need a wide solution stencil. Variable coefficients require their derivatives and mixed terms to be treated consistently; the constant-coefficient identity cannot be reused unchanged for a different elliptic operator. On irregular meshes, conservation and consistent fluxes may be more useful starting points than a symmetric Cartesian formula.
Finally, discretization and solution cost are coupled. The five-point Dirichlet matrix has eigenvalues proportional to sums of squared sine frequencies, so its smallest eigenvalue stays of order one while its largest is . Its condition number grows like ; simple relaxation therefore becomes slow. Sparse direct elimination, conjugate gradient method with appropriate matrix preconditioning, and the multigrid method are alternatives. A sound design combines local accuracy, boundary fidelity, mesh-independent stability, and an algebraic solver whose residual is small enough for the intended error tolerance.
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