This book focuses on solutions of second order, linear, parabolic, partial differentialequations on an infinite strip-emphasizing their integral representation, their initialvalues in several senses, and the relations between these.Parabolic Equations on an Infinite Strip provides valuable information-previously unavailable in a single volume-on such topics as semigroup property.. . the Cauchy problem ... Gauss-Weierstrass representation . .. initial limits .. .normal limits and related representation theorems ... hyperplane conditions .. .determination of the initial measure .. . and the maximum principle. It also exploresnew, unpublished results on parabolic limits . . . more general limits ... and solutionssatisfying LP conditions.Requiring only a fundamental knowledge of general analysis and measure theory, thisbook serves as an excellent text for graduate students studying partial differentialequations and harmonic analysis, as well as a useful reference for analysts interested inapplied measure theory, and specialists in partial differential equations.

In an effort to improve the error analysis of numerical methods for time-dependent PDEs and obtain reasonable error estimates, Sun developed the concept of numerical smoothness in [29] and [30]. In this dissertation, we prepare the framework for applying numerical smoothness to the error analysis for parabolic equations. The Discontinuous Galerkin (DG) method for solving parabolic equations is considered to be a successful scheme, but the error analysis for the method is limited. To provide the framework, we focus on a class of primal DG methods, namely variations of interior penalty methods. The numerical smoothness technique is used to perform an error analysis for a method in this class known as the Symmetric Interior Penalty Galerkin (SIPG) method. We take our model problem to be the one dimensional heat equation with Dirichlet boundary conditions. Therefore, this work represents a first step in applying Sun's numerical smoothness technique to the error analysis of parabolic equations. Two examples are provided to show how our numerical smoothness indicators can be used. Concluding remarks discuss how this early stage may be expanded to more complex parabolic equations and other numerical schemes.

This Chapter aims to investigate the error estimation of numerical approximation to a class of semilinear parabolic problems. More specifically, the time discretization uses the backward Euler Galerkin method and the space discretization uses the finite element method for which the meshes are allowed to change in time. The key idea in our analysis is to adapt the elliptic reconstruction technique, introduced by Makridakis and Nochetto 2003, enabling us to use the a posteriori error estimators derived for elliptic models and to obtain optimal order in L,àûH1 for Lipschitz and non-Lipschitz nonlinearities. In this Chapter, some challenges will be addressed to deal with nonlinear term by employing a continuation argument.