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Computerphysik: Problemlösung mit Python Taschenbuch
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Computerphysik: Problemlösung mit Python Taschenbuch
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Computerphysik: Problemlösung mit Python Taschenbuch

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    Book Title
    Computational Physics : Problem Solving with Python Paperback
    ISBN
    9783527413157
    Kategorie

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    Product Identifiers

    Publisher
    Wiley & Sons, Incorporated, John
    ISBN-10
    3527413154
    ISBN-13
    9783527413157
    eBay Product ID (ePID)
    210326487

    Product Key Features

    Number of Pages
    644 Pages
    Language
    English
    Publication Name
    Computational Physics : Problem Solving with Python
    Publication Year
    2015
    Subject
    Physics / Mathematical & Computational, Programming Languages / Python
    Type
    Textbook
    Subject Area
    Computers, Science
    Author
    Rubin H. Landau, Cristian C. Bordeianu, Manuel J. Páez
    Format
    Trade Paperback

    Dimensions

    Item Height
    1.3 in
    Item Weight
    43.6 Oz
    Item Length
    9.6 in
    Item Width
    6.7 in

    Additional Product Features

    Edition Number
    3
    Intended Audience
    Scholarly & Professional
    Dewey Edition
    23
    Illustrated
    Yes
    Dewey Decimal
    530.0113
    Synopsis
    The use of computation and simulation has become an essential part of the scientific process. Being able to transform a theory into an algorithm requires significant theoretical insight, detailed physical and mathematical understanding, and a working level of competency in programming., The important aspects of computational modelling is the combination of science, mathematics and computation. Programming is part of that, and in this book the authors employ Python, which is considered as one of the easiest and most accessible language for beginning programming, and commonly used for interactive and exploratory computations in scientific research. From the contents: Computing software basics and Python libraries Errors and uncertainties in computations Monte Carlo: Randomness, walks, decays, thermodynamics Differentiation, integration, matrix computing Trial-and-error searching and data fitting Solving ordinary differential equations with applications High-performance hardware and programming Fourier, wavelet and principal component analyses Nonlinear dynamics Fractals and Statistical growth models Molecular dynamics Partial Differential Equations: heat, waves, E-M, quantum wavepackets Electrostatics via finite elements Shock waves, solitons and fluid dynamics Feynman path integrals and integral equations of quantum mecha, The use of computation and simulation has become an essential part of the scientific process. Being able to transform a theory into an algorithm requires significant theoretical insight, detailed physical and mathematical understanding, and a working level of competency in programming. This upper-division text provides an unusually broad survey of the topics of modern computational physics from a multidisciplinary, computational science point of view. Its philosophy is rooted in learning by doing (assisted by many model programs), with new scientific materials as well as with the Python programming language. Python has become very popular, particularly for physics education and large scientific projects. It is probably the easiest programming language to learn for beginners, yet is also used for mainstream scientific computing, and has packages for excellent graphics and even symbolic manipulations. The text is designed for an upper-level undergraduate or beginning graduate course and provides the reader with the essential knowledge to understand computational tools and mathematical methods well enough to be successful. As part of the teaching of using computers to solve scientific problems, the reader is encouraged to work through a sample problem stated at the beginning of each chapter or unit, which involves studying the text, writing, debugging and running programs, visualizing the results, and the expressing in words what has been done and what can be concluded. Then there are exercises and problems at the end of each chapter for the reader to work on their own (with model programs given for that purpose).
    LC Classification Number
    QC52

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