%%here we use LaTeX2e and AMSLaTeX \documentclass[12pt]{article} \usepackage{amsmath,amsthm,latexsym,amsfonts,amssymb} \newcommand{\ttfrac}[2]{\frac{\textstyle #1} {\textstyle #2}} %%the following has been adjusted for our laser print and may be different %%for your laser print. \topmargin -1.5cm \oddsidemargin -0.35in %%end of local settings. %% \textwidth 185mm \textheight 241mm \begin{document} \begin{center} \textbf{\Large INCREMENTAL UNKNOWNS} \\ \ \\ \textbf{\Large AND} \\ \ \\ \textbf{\Large GRAPH TECHNIQUES} \end{center} \ \begin{center} Salvador Garcia \\ Instituto de Matem\'aticas y F\'{\i}sica \\ Universidad de Talca \\ Casilla 721, Talca, Chile \\ E-mail: sgarcia@pehuenche.utalca.cl \end{center} \ \begin{center} \textbf{\Large Summary} \end{center} \ \qquad The condition number of the incremental unknowns matrix associated to the Laplace operator is $ O(1/h_{0}^{2}) O((\log h)^{2}) $ where $ h_{0} $ is the mesh size of the coarsest grid and where $ h $ is the mesh size of the finest grid. Furthermore, if block diagonal scaling is used then the condition number of the preconditioned incremental unknowns matrix associated to the Laplace operator comes out to be $ O((\log h)^{2}) $. \ \qquad Incremental unknowns were introduced by Temam (1990) in the dynamical system theory where the objective is to study the long-term dynamic behavior of the solutions of dissipative evolutionary equations when finite-difference approximations in a variational framework of such equations are used and when several levels of discretization are considered. On the whole, a general elliptic linear differential equation has to be solved at each time step; incremental unknowns are efficient in the numerical solution of such equations but no rigorous theoretical justification was available. Hereafter, using graph techniques, we prove that the condition number of the incremental unknowns matrix associated to the Laplace operator is $ O(1/h_{0}^{2}) O((\log h)^{2}) $ where $ h_{0} $ is the mesh size of the coarsest grid and where $ h $ is the mesh size of the finest grid; furthermore, if block diagonal scaling is used then the condition number of the preconditioned incremental unknowns matrix associated to the Laplace operator comes out to be $ O((\log h)^{2}) $. \ \qquad The results are obtained in essence by deriving appropriate bounds on the generalized Rayleigh quotient \begin{equation*} \ttfrac{(v,h^{2}(-\Delta_{h})v)}{(v,(S\mathcal{K}^{-1}S^{T})^{-1}v)}, \end{equation*} as stated by Elman and Zhang (1995); here $ \Delta_{h} $ is the finite-difference Laplace operator and $ \mathcal{K} $ is either the identity or a block diagonal part of the incremental unknowns matrix $ S^{T} (-\Delta_{h}) S $, where $ S $ stands for the transfer matrix from the incremental unknowns $ \hat{x} $ to the nodal unknowns $ x $, i.e., $ x = S \hat{x} $; the coefficients of this incremental unknowns matrix are computed (bounded) using the finite-difference variational approach. It follows promptly from linear algebra lemmas and from the Ger\v{s}gorin theorem that the maximum eigenvalue of the incremental unknowns matrix $ S^{T} (-\Delta_{h}) S $ is bounded by an absolute constant independent of $ i $ (the number of levels); then we infer the result stated before. \end{document}