Introduction to Numerical Programming

A Practical Guide for Scientists and Engineers Using Python and C/C++
1. Auflage 2014
ISBN: 978-1-4665-6967-6
Verlag: CRC Press

Buch, Englisch, 674 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 1246 g

Reihe: Series in Computational Physics

Makes Numerical Programming More Accessible to a Wider Audience

Bearing in mind the evolution of modern programming, most specifically emergent programming languages that reflect modern practice, Numerical Programming: A Practical Guide for Scientists and Engineers Using Python and C/C++ utilizes the author’s many years of practical research and teaching experience to offer a systematic approach to relevant programming concepts. Adopting a practical, broad appeal, this user-friendly book offers guidance to anyone interested in using numerical programming to solve science and engineering problems. Emphasizing methods generally used in physics and engineering—from elementary methods to complex algorithms—it gradually incorporates algorithmic elements with increasing complexity.

Develop a Combination of Theoretical Knowledge, Efficient Analysis Skills, and Code Design Know-How

The book encourages algorithmic thinking, which is essential to numerical analysis. Establishing the fundamental numerical methods, application numerical behavior and graphical output needed to foster algorithmic reasoning, coding dexterity, and a scientific programming style, it enables readers to successfully navigate relevant algorithms, understand coding design, and develop efficient programming skills. The book incorporates real code, and includes examples and problem sets to assist in hands-on learning.

- Begins with an overview on approximate numbers and programming in Python and C/C++, followed by discussion of basic sorting and indexing methods, as well as portable graphic functionality

- Contains methods for function evaluation, solving algebraic and transcendental equations, systems of linear algebraic equations, ordinary differential equations, and eigenvalue problems

- Addresses approximation of tabulated functions, regression, integration of one- and multi-dimensional functions by classical and Gaussian quadratures, Monte Carlo integration techniques, generation of random variables, discretization methods for ordinary and partial differential equations, and stability analysis

This text introduces platform-independent numerical programming using Python and C/C++, and appeals to advanced undergraduate and graduate students in natural sciences and engineering, researchers involved in scientific computing, and engineers carrying out applicative calculations.

Zielgruppe

This text serves advanced undergraduate and graduate level students in physical sciences and engineering, as well as researchers and professionals in various disciplines of science and engineering who employ computational tools in their study and work.

Autoren/Hrsg.

Beu, Titus A.

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik Mathematik Mathematik Allgemein Zahlensysteme
• Naturwissenschaften Physik Physik Allgemein

Inhaltsverzeichnis

Approximate Numbers. Basic Programming Techniques. Elements of Scientific Graphics. Sorting and Indexing. Evaluation of Functions. Algebraic and Transcendental Equations. Systems of Linear Equations. Eigenvalue Problems. Modeling of Tabulated Functions. Integration of Functions. Monte Carlo Method. Ordinary Differential Equations. Partial Differential Equations. Appendices. Index.

Über Autor(innen)

Titus Adrian Beu, professor of theoretical and computational physics at the University Babes-Bolyai from Cluj-Napoca, Romania, has been active in the broader field of computational physics for more than 30 years. His research topics have evolved from Tokamak plasma and nuclear reactor calculations in the 1980s, collision theory and molecular cluster spectroscopy in the 1990s, to fullerenes and nanofluidics simulations in recent years. Development of ample computer codes has been at the core of all research projects the author has conducted. In parallel, he has lectured on general programming techniques and advanced numerical methods, general simulation methods, and advanced molecular dynamics.