Let and , and define the scaled forward difference operator, backward difference operator and second-order central difference by
The two finite difference methods are the nonlinear systems
with the prescribed Dirichlet boundary conditions and . These equations determine the interior nodal values.
For clarity distinguish the interior and edge inner products and their norms:
The bracketed norm includes the last edge . Let , so , and put for . Direct telescoping gives discrete summation by parts:
Subtract the two nonlinear systems, multiply each equation by and sum. The resulting discrete energy identity is
The nonlinear summands are nonnegative by the factorization in (a). Using Young's inequality for products at every node gives
This also proves uniqueness of each discrete solution. Existence can be seen by minimizing, with the endpoints fixed, the strictly convex energy functional
It is a coercive function of its finitely many interior values, so it attains a minimum. Its first derivatives are ; thus its minimizer solves the scheme. The same argument applies to .
On the vector space of nodal values with zero endpoints define the discrete Sobolev norm
It is a norm because it is the Euclidean norm of the scaled list of nodal values and first finite differences, and vanishes only for the zero list. It is the discrete counterpart of the Sobolev space norm. Here has zero endpoints, so this definition applies directly.
Set , finite by the assumed continuity. Taylor's theorem with fourth-order remainders gives, for suitable and ,
Adding the two expansions cancels the odd derivatives, so
Consequently . Doubling the bound in (c) gives , and therefore
Thus is a valid nonnegative constant. To satisfy the request for a strictly positive constant even when , take , independent of . This proves second-order convergence of a numerical method in a discrete Sobolev norm, including control of the backward difference operator applied to the error.