Introduction to the Tools of Scientific Computing

The book provides an introduction to common programming tools and methods in numerical mathematics and scientific computing. Unlike standard approaches, it does not focus on any specific language, but aims to explain the underlying ideas.

Typically, new concepts are first introduced in the particularly user-friendly Python language and then transferred and extended in various programming environments from C/C++, Julia and MATLAB to Maple and Mathematica. This includes various approaches to distributed computing. By examining and comparing different languages, the book is also helpful for mathematicians and practitioners in deciding which programming language to use for which purposes.

At a more advanced level, special tools for the automated solution of partial differential equations using the finite element method are discussed. On a more experimental level, the basic methods of scientific machine learning in artificial neural networks are explained and illustrated.

Surveys and compares many different programming languages Helps to decide which programming language to use for which purpose Programming concepts are introduced in well-known mathematical contexts

Autorentext
Einar Smith holds academic degrees in Mathematics from the Unversity of Bonn, in Economics from the University of Oslo, and in Computer Science from the University of Hamburg. He has published a textbook on Mathematical Computability Theory, and a biography of the German computer scientist C.A. Petri. Both books have been published by Springer. In recent years he has mainly been concerned with the teaching of numerical methods at the University of Bonn, with an emphasis on computer programming.

Inhalt
Introduction.- Part I, Background.- Part II, Core Languages.- Part III, Commercial Computing Environments.- Part IV, Distributed Computing.- Part V, Specialized Programming Environments.- References.- Index.