Peter Deuflhard

Andreas Hohmann

A First Course in Scientific Computation

Numerical Analysis

Eine algorithmisch orientierte Einführung

Folkmar Bornemann

Die vierte, durchgesehene und ergänzte Auflage dieses Standardlehrbuchs folgt weiterhin konsequent der Linie, den Leser auf solider theoretischer Basis direkt zu praktisch bewährten Methoden zu führen - von der Herleitung über die Analyse bis hin zu Fragen der Implementierung. Dies macht das Buch sowohl für Mathematiker als auch für Naturwissenschaftler und Ingenieure attraktiv. Das Lehrbuch eignet sich als Vorlesungsbegleitung für Studierende ebenso wie zum Selbststudium für im Beruf stehende Naturwissenschaftler. Es setzt lediglich Grundkenntnisse der Analysis (entsprechend Vorlesung Höhere Mathematik bei Physikern und Ingenieuren) sowie der Numerischen Mathematik (Einführungsvorlesung) voraus.

Gewöhnliche Differentialgleichungen

This book introduces the main topics of modern numerical analysis: sequence of linear equations, error analysis, least squares, nonlinear systems, symmetric eigenvalue problems, three-term recursions, interpolation and approximation, large systems and numerical integrations. The presentation draws on geometrical intuition wherever appropriate and is supported by a large number of illustrations, exercises, and examples.

An Introduction

Numerical Analysis in Modern Scientific Computing

Dietmar Hömberg

Martin Grötschel

Mathematics: intellectual endeavor, production factor, key technology, key to key technologies? Mathematics is all of these; the last three of its facets are not well known, though. They have been the focus of the research and development in the Berlin-based DFG Research Center MATHEON in the last twelve years. Through these activities, MATHEON has become an international trademark. Its mission and its strategies for carrying out creative, application-driven research in mathematics and cooperating in the solution of complex problems in key technologies are by now a role model for the development of many other centers. Modern key technologies have become highly sophisticated, integrating aspects of engineering, computer, business and other sciences. At the same time, the innovation cycles get shorter and shorter. These simultaneous challenges can be mastered only by qualitatively and quantitatively rigorous methods. And that is where mathematics is indispensable. Flexible mathematical models, as well as fast and accurate methods for numerical simulation and optimization, open new possibilities to handle the indicated complexities, to react quickly, and to explore new options. Researchers in mathematical fields such as optimization, discrete mathematics, numerical analysis, scientific computing, applied analysis and stochastic analysis have to work hand in hand with scientists and engineers to fully exploit this potential and to strengthen the transversal role of mathematics in solving the challenging problems in key technologies. This book presents in seven chapters the research highlights of the research work carried out in the MATHEON application areas: Life Sciences, Networks, Production, Electronic and Photonic Devices, Finance, Visualization, and Education. The chapters summarize many of the contributions, put them in the context of current mathematical research activities, and outline their impact in various key technologies. To make some of the results more easily accessible to the general public, a large number of ``showcases'' are presented that illustrate a few success stories.

Mathematics for Key Technologies

MATHEON

Martin Weiser

Thistextbook expands the standard work on numerical mathematics to include the numerics of partial differential equations. The volume is intended for students of mathematics as well as physicists, chemists and engineers who are confronted with finding efficient solutions for complex application problems."

adaptive Lösung partieller Differentialgleichungen

Numerische Mathematik 3

Well-known authors; Includes topics and results that have previously not been covered in a book; Uses many interesting examples from science and engineering; Contains numerous homework exercises; Scientific computing is a hot and topical area

Scientific Computing with Ordinary Differential Equations

Numerical mathematics is a subtopic of scientific computing. The focus lies on the efficiency of algorithms, i.e. speed, reliability, and robustness. This leads to adaptive algorithms. The theoretical derivation und analyses of algorithms are kept as elementary as possible in this book; the needed sligtly advanced mathematical theory is summarized in the appendix. Numerous figures and illustrating examples explain the complex data, as non-trivial examples serve problems from nanotechnology, chirurgy, and physiology. The book addresses students as well as practitioners in mathematics, natural sciences, and engineering. It is designed as a textbook but also suitable for self study.

Peter Deuflhard

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