Computational Physics
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Computational Physics
"Computational Physics: Basic Concepts" serves as an indispensable guide for students, researchers, and enthusiasts exploring the intersection of physics and computational methods. This book offers a comprehensive exploration of the fundamental principles of computational physics, providing a solid foundation to tackle complex problems in various branches of physics. The book begins by elucidating the foundational principles and theoretical underpinnings essential for effective computational simulations. It covers a variety of numerical techniques, including finite difference methods and Monte Carlo simulations, with practical examples and applications. Recognizing the importance of coding skills, it includes a section on programming tailored for physicists, teaching readers to implement numerical algorithms using popular programming languages. "Computational Physics: Basic Concepts" extends its coverage to diverse branches of physics such as classical mechanics, electromagnetism, quantum mechanics, and statistical physics, illustrating the versatility of computational techniques. Each chapter includes problem-solving exercises designed to reinforce understanding and enhance computational skills. Techniques for data visualization and interpretation are discussed, enabling effective communication of findings. The book also shares practical tips and best practices to optimize computational workflows and avoid common pitfalls. Whether you're a student new to computational physics or a seasoned researcher, "Computational Physics: Basic Concepts" provides a thorough and accessible resource for mastering the essential elements of this dynamic field.
Computational Physics, Vol I
Author: Konstantinos N. Anagnostopoulos
language: en
Publisher: Konstantinos Anagnostopoulos
Release Date: 2014-07-27
This book is an introduction to the computational methods used in physics and other scientific fields. It is addressed to an audience that has already been exposed to the introductory level of college physics, usually taught during the first two years of an undergraduate program in science and engineering. The book starts with very simple problems in particle motion and ends with an in-depth discussion of advanced techniques used in Monte Carlo simulations in statistical mechanics. The level of instruction rises slowly, while discussing problems like the diffusion equation, electrostatics on the plane, quantum mechanics and random walks. The book aims to provide the students with the background and the experience needed in order to advance to high performance computing projects in science and engineering. But it also tries to keep the students motivated by considering interesting applications in physics, like chaos, quantum mechanics, special relativity and the physics of phase transitions. The book and the accompanying software is available for free in electronic form at http://goo.gl/SGUEkM (www.physics.ntua.gr/%7Ekonstant/ComputationalPhysics) and a printed copy can be purchased from lulu.com at http://goo.gl/Pg1zHc (vol II at http://goo.gl/XsSBdP )
Computational Physics
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).
