Wolfgang Hackbusch

In the second edition of this classic monograph, complete with four new chapters and updated references, readers will now have access to content describing and analysing classical and modern methods with emphasis on the algebraic structure of linear iteration, which is usually ignored in other literature. The necessary amount of work increases dramatically with the size of systems, so one has to search for algorithms that most efficiently and accurately solve systems of, e.g., several million equations. The choice of algorithms depends on the special properties the matrices in practice have. An important class of large systems arises from the discretization of partial differential equations. In this case, the matrices are sparse (i.e., they contain mostly zeroes) and well-suited to iterative algorithms. The first edition of this book grew out of a series of lectures given by the author at the Christian-Albrecht University of Kiel to students of mathematics. The second edition includes quite novel approaches.

Iterative Solution of Large Sparse Systems of Equations

Multi-grid methods are the most efficient tools for solving elliptic boundary value problems. The reader finds here an elementary introduction to multi-grid algorithms as well as a comprehensive convergence analysis. One section describes special applications (convection-diffusion equations, singular perturbation problems, eigenvalue problems, etc.). The book also contains a complete presentation of the multi-grid method of the second kind, which has important applications to integral equations (e.g. the "panel method") and to numerous other problems. Readers with a practical interest in multi-grid methods will benefit from this book as well as readers with a more theoretical interest.

Multi-Grid Methods and Applications

Die Integralgleichungen stellen ein Gebiet dar. das für sich durchaus selbständig ist und auf einer interessanten Mischung von Analysis. Funktionentheorie und Funktionalanalysis beruht. Auf der anderen Seite gewinnen die Integralgleichungen ihr praktisches Interesse aus der «Integralgleichungsmethode». die es erlaubt, partielle Differential gleichungen in Integralgleichungen umzuformen. Das Buch ist aus Vorlesungen hervorgegangen, die der Autor an der Ruhr-Universität Bochum und der Christian-Albrechts-Universität Kiel gehalten hat. Der Umfang der Kapitel 1 bis 6 entspricht etwa einer intensiven vierstündigen Vorlesung. Das Studium der Integral gleichungen kann mit Vorkenntnissen der Analysis und den Grundlagen der Numerik aufgenommen werden. Kenntnisse aus der Funktional analysis sind hilfreich. aber nicht unabdingbar, wenn Grundbegriffe wie Banach-und Hilbert-Räume geläufig sind. Der Theorieteil dieses Buches ist so knapp wie möglich bemessen. da die Numerik in den Kapiteln 2. 4, 5 im Vordergrund stehen soll. Wichtige Teile der benötigten Funktionalanalysis wie etwa die Riesz-Schauder-Theorie werden ohne Herleitung wiedergegeben. Es wird dabei davon ausgegangen. daß dem Leser dieses Gebiet entweder aus einer Vorlesung über «Funktionalanalysis» bekannt ist oder daß e- mit gesteigerter Motivation durch praktische Beispiele - diese Kapitel durch Vorlesungen oder Lektüre nachholen wird. Es sei daran erinnert. daß auch historisch die Funktionalanalysis aus der Diskussion der Integralgleichungen hervorgegangen ist. Als Funktionenräume werden in dieser Darstellung vornehmlich die klassischen der stetigen oder Hölder-stetigen Funktionen verwendet. Die Sobolev-Räume werden weitgehend vermieden. was zum Beispiel zur Folge hat. daß die Integraloperatoren hier nicht in der erforderlichen Allgemeinheit als Pseudodifferentialoperatoren diskutiert werden können.

Theorie und Numerik

Integralgleichungen

Ulrich Trottenberg

Proceedings of the 2nd European Conference on Multigrid Methods Held at Cologne, October 1-4, 1985

Multigrid Methods II

In this book, the author compares the meaning of stability in different subfields of numerical mathematics. Concept of Stability in numerical mathematics opens by examining the stability of finite algorithms. A more precise definition of stability holds for quadrature and interpolation methods, which the following chapters focus on. The discussion then progresses to the numerical treatment of ordinary differential equations (ODEs). While one-step methods for ODEs are always stable, this is not the case for hyperbolic or parabolic differential equations, which are investigated next. The final chapters discuss stability for discretisations of elliptic differential equations and integral equations. In comparison among the subfields we discuss the practical importance of stability and the possible conflict between higher consistency order and stability.

The Concept of Stability in Numerical Mathematics

This book simultaneously presents the theory and the numerical treatment of elliptic boundary value problems, since an understanding of the theory is necessary for the numerical analysis of the discretisation. It first discusses the Laplace equation and its finite difference discretisation before addressing the general linear differential equation of second order. The variational formulation together with the necessary background from functional analysis provides the basis for the Galerkin and finite-element methods, which are explored in detail. A more advanced chapter leads the reader to the theory of regularity. Individual chapters are devoted to singularly perturbed as well as to elliptic eigenvalue problems. The book also presents the Stokes problem and its discretisation as an example of a saddle-point problem taking into account its relevance to applications in fluid dynamics.

Theory and Numerical Treatment

Elliptic Differential Equations

M. T. Schlick

Derived from a lecture series for college mathematics students, introduces the methods of dealing with elliptical boundary-value problems--both the theory and the numerical analysis. Includes exercises. Translated and somewhat expanded from the 1987 German version. Annotation copyright by Book News, Inc., Portland, OR

Peter Monk

Carsten Carstensen

Stefan Funken

Ronald W. Hoppe

The dimmed outlines of phenomenal things all into one another unless we put on the merge focusing-glass of theory, and screw it up some times to one pitch of definition and sometimes to another, so as to see down into different depths through the great millstone of the world James Clerk Maxwell (1831 - 1879) For a long time after the foundation of the modern theory of electromag netism by James Clerk Maxwell in the 19th century, the mathematical ap proach to electromagnetic field problems was for a long time dominated by the analytical investigation of Maxwell's equations. The rapid development of computing facilities during the last century has then necessitated appropriate numerical methods and algorithmic tools for the simulation of electromagnetic phenomena. During the last few decades, a new research area "Computational Electromagnetics" has emerged com prising the mathematical analysis, design, implementation, and application of numerical schemes to simulate all kinds of relevant electromagnetic pro cesses. This area is still rapidly evolving with a wide spectrum of challenging issues featuring, among others, such problems as the proper choice of spatial discretizations (finite differences, finite elements, finite volumes, boundary elements), fast solvers for the discretized equations (multilevel techniques, domain decomposition methods, multipole, panel clustering), and multiscale aspects in microelectronics and micromagnetics.

Proceedings of the GAMM Workshop on Computational Electromagnetics, Kiel, Germany, January 26–28, 2001

Computational Electromagnetics

Special numerical techniques are already needed to deal with nxn matrices for large n.Tensor data are of size nxnx...xn=n^d, where n^d exceeds the computer memory by far. They appear for problems of high spatial dimensions. Since standard methods fail, a particular tensor calculus is needed to treat such problems. The monograph describes the methods how tensors can be practically treated and how numerical operations can be performed. Applications are problems from quantum chemistry, approximation of multivariate functions, solution of pde, e.g., with stochastic coefficients, etc. ​

Tensor Spaces and Numerical Tensor Calculus

This self-contained monograph presents matrix algorithms and their analysis. The new technique enables not only the solution of linear systems but also the approximation of matrix functions, e.g., the matrix exponential. Other applications include the solution of matrix equations, e.g., the Lyapunov or Riccati equation. The required mathematical background can be found in the appendix. The numerical treatment of fully populated large-scale matrices is usually rather costly. However, the technique of hierarchical matrices makes it possible to store matrices and to perform matrix operations approximately with almost linear cost and a controllable degree of approximation error. For important classes of matrices, the computational cost increases only logarithmically with the approximation error. The operations provided include the matrix inversion and LU decomposition. Since large-scale linear algebra problems are standard in scientific computing, the subject of hierarchical matrices is of interest to scientists in computational mathematics, physics, chemistry and engineering.

Wolfgang Hackbusch

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