Lectures On Numerical Methods

The present book is an edition of the manuscripts to the courses "Numerical Methods I" and "Numerical Mathematics I and II" which Professor H. Rutishauser held at the E.T.H. in Zurich. The first-named course was newly conceived in the spring semester of 1970, and intended for beginners, while the two others were given repeatedly as elective courses in the sixties. For an understanding of most chapters the funda mentals of linear algebra and calculus suffice. In some places a little complex variable theory is used in addition. However, the reader can get by without any knowledge of functional analysis. The first seven chapters discuss the direct solution of systems of linear equations, the solution of nonlinear systems, least squares prob lems, interpolation by polynomials, numerical quadrature, and approxima tion by Chebyshev series and by Remez' algorithm. The remaining chapters include the treatment of ordinary and partial differential equa tions, the iterative solution of linear equations, and a discussion of eigen value problems. In addition, there is an appendix dealing with the qd algorithm and with an axiomatic treatment of computer arithmetic.

When Herb Keller suggested, more than two years ago, that we update our lectures held at the Tata Institute of Fundamental Research in 1977, and then have it published in the collection Springer Series in Computational Physics, we thought, at first, that it would be an easy task. Actually, we realized very quickly that it would be more complicated than what it seemed at first glance, for several reasons: 1. The first version of Numerical Methods for Nonlinear Variational Problems was, in fact, part of a set of monographs on numerical mat- matics published, in a short span of time, by the Tata Institute of Fun- mental Research in its well-known series Lectures on Mathematics and Physics; as might be expected, the first version systematically used the material of the above monographs, this being particularly true for Lectures on the Finite Element Method by P. G. Ciarlet and Lectures on Optimization—Theory and Algorithms by J. Cea. This second version had to be more self-contained. This necessity led to some minor additions in Chapters I-IV of the original version, and to the introduction of a chapter (namely, Chapter Y of this book) on relaxation methods, since these methods play an important role in various parts of this book.

This book differs from traditional numerical analysis texts in that it focuses on the motivation and ideas behind the algorithms presented rather than on detailed analyses of them. It presents a broad overview of methods and software for solving mathematical problems arising in computational modeling and data analysis, including proper problem formulation, selection of effective solution algorithms, and interpretation of results.? In the 20 years since its original publication, the modern, fundamental perspective of this book has aged well, and it continues to be used in the classroom. This Classics edition has been updated to include pointers to Python software and the Chebfun package, expansions on barycentric formulation for Lagrange polynomial interpretation and stochastic methods, and the availability of about 100 interactive educational modules that dynamically illustrate the concepts and algorithms in the book. Scientific Computing: An Introductory Survey, Second Edition is intended as both a textbook and a reference for computationally oriented disciplines that need to solve mathematical problems.

The aim of this book is to provide a simple and useful introduction for the fresh students into the vast field of numerical analysis. Like any other introductory course on numerical analysis, this book contains the basic theory, which in the present text refers to the following topics: linear equations, nonlinear equations, eigensystems, interpolation, approximation of functions, numerical differentiation and integration, stochastics, ordinary differential equations and partial differential equations. Because the students need to quickly understand why the numerical methods correctly work, the proofs of theorems were shorted as possible, insisting more on ideas than on a lot of algebra manipulation. The included examples are presented with a minimum of complications, emphasizing the steps of the algorithms. The numerical methods described in this book are illustrated by computer programs written in C. Our goal was to develop very simple programs which are easily to read and understand by students. Also, the programs should run without modification on any compiler that implements the ANSI C standard. Because our intention was to easily produce screen input-output (using, scanf and printf), in case of WINDOWS visual programming environments, like Visual C++ (Microsoft) and Borland C++ Builder, the project should be console-application. This will be not a problem for DOS and LINUX compilers. If this material is used as a teaching aid in a class, I would appreciate if under such circumstances, the instructor of such a class would send me a note at the address below informing me if the material is useful. Also, I would appreciate any suggestions or constructive criticism regarding the content of these lecture notes.

The course of lectures on numerical methods (part I) given by the author to students in the numerical third of the course of the mathematics mechanics department of Leningrad State University is set down in this volume. Only the topics which, in the opinion of the author, are of the greatest value for numerical methods are considered in this book. This permits making the book comparatively small in size, and, the author hopes, accessible to a sufficiently wide circle of readers. The book may be used not only by students in daily classes, but also by students taking correspondence courses and persons connected with practical computa tion who desire to improve their theoretical background. The author is deeply grateful to V. I. Krylov, the organizer ofthe course on numerical methods (part I) at Leningrad State University, for his considerable assistance and constant interest in the work on this book, and also for his attentive review of the manuscript. The author is very grateful to G. P. Akilov and I. K. Daugavet for a series of valuable suggestions and observations. The Author Chapter I NUMERICAL SOLUTION OF EQUATIONS In this chapter, methods for the numerical solution of equations of the form P(x) = 0, will be considered, where P(x) is in general a complex-valued function.

These notes developed from a course on the numerical solution of conservation laws first taught at the University of Washington in the fall of 1988 and then at ETH during the following spring. The overall emphasis is on studying the mathematical tools that are essential in de veloping, analyzing, and successfully using numerical methods for nonlinear systems of conservation laws, particularly for problems involving shock waves. A reasonable un derstanding of the mathematical structure of these equations and their solutions is first required, and Part I of these notes deals with this theory. Part II deals more directly with numerical methods, again with the emphasis on general tools that are of broad use. I have stressed the underlying ideas used in various classes of methods rather than present ing the most sophisticated methods in great detail. My aim was to provide a sufficient background that students could then approach the current research literature with the necessary tools and understanding. vVithout the wonders of TeX and LaTeX, these notes would never have been put together. The professional-looking results perhaps obscure the fact that these are indeed lecture notes. Some sections have been reworked several times by now, but others are still preliminary. I can only hope that the errors are not too blatant. Moreover, the breadth and depth of coverage was limited by the length of these courses, and some parts are rather sketchy.

A logically organized advanced textbook, which turns the reader into an active participant by asking questions, hinting, giving direct recommendations, comparing different methods, and discussing "pessimistic" and "optimistic" approaches to numerical analysis. Advanced students and graduate students majoring in computer science, physics and mathematics will find this book helpful.