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an introduction to computational physics: An Introduction to Computational Physics Tao Pang, 1997-09-28 Textbook introducing basic methods of computational physics and giving overview of several advanced topics; for advanced undergraduate or beginning graduate students. |
an introduction to computational physics: Introduction to Computational Physics for Undergraduates Omair Zubairi, Fridolin Weber, 2018-04-04 This is an introductory textbook on computational methods and techniques intended for undergraduates at the sophomore or junior level in the fields of science, mathematics, and engineering. It provides an introduction to programming languages such as FORTRAN 90/95/2000 and covers numerical techniques such as differentiation, integration, root finding, and data fitting. The textbook also entails the use of the Linux/Unix operating system and other relevant software such as plotting programs, text editors, and mark up languages such as LaTeX. It includes multiple homework assignments. |
an introduction to computational physics: Introductory Computational Physics Andi Klein, Alexander Godunov, 2006-03-09 Computers are one of the most important tools available to physicists, whether for calculating and displaying results, simulating experiments, or solving complex systems of equations. Introducing students to computational physics, this textbook, first published in 2006, shows how to use computers to solve mathematical problems in physics and teaches students about choosing different numerical approaches. It also introduces students to many of the programs and packages available. The book relies solely on free software: the operating system chosen is Linux, which comes with an excellent C++ compiler, and the graphical interface is the ROOT package available for free from CERN. This broad scope textbook is suitable for undergraduates starting on computational physics courses. It includes exercises and many examples of programs. Online resources at www.cambridge.org/0521828627 feature additional reference information, solutions, and updates on new techniques, software and hardware used in physics. |
an introduction to computational physics: A Survey of Computational Physics Rubin Landau, José Páez, Cristian C. Bordeianu, 2011-10-30 Computational physics is a rapidly growing subfield of computational science, in large part because computers can solve previously intractable problems or simulate natural processes that do not have analytic solutions. The next step beyond Landau's First Course in Scientific Computing and a follow-up to Landau and Páez's Computational Physics, this text presents a broad survey of key topics in computational physics for advanced undergraduates and beginning graduate students, including new discussions of visualization tools, wavelet analysis, molecular dynamics, and computational fluid dynamics. By treating science, applied mathematics, and computer science together, the book reveals how this knowledge base can be applied to a wider range of real-world problems than computational physics texts normally address. Designed for a one- or two-semester course, A Survey of Computational Physics will also interest anyone who wants a reference on or practical experience in the basics of computational physics. Accessible to advanced undergraduates Real-world problem-solving approach Java codes and applets integrated with text Companion Web site includes videos of lectures |
an introduction to computational physics: Computational Physics R. C. Verma, 2007 Personal Computers Have Become An Essential Part Of The Physics Curricula And Is Becoming An Increasingly Important Tool In The Training Of Students. The Present Book Is An Effort To Provide A Quality And Classroom Tested Resource Material.Salient Features * Topics Have Been Carefully Selected To Give A Flavour Of Computational Techniques In The Context Of A Wide Range Of Physics Problems. * Style Of Presentation Emphasis The Pedagogic Approach, Assuming No Previous Knowledge Of Either Programming In High-Level Language Or Numerical Techniques. * Profusely Illustrated With Diagrams, Graphic Outputs, Programming Hints, Algorithms And Source Codes. * Ideally Suited For Self-Study With A Pc On Desktop. * Accompanied With A Cd Rom With Source Codes Of Selected Problems Saving The User From Typing In The Source Code. * Can Be Adopted As A Two-Semester Course In Universities Running Courses Such As Computer Applications In Physics, Numerical Methods In Physics Or As An Additional Optional Paper In Nodal Centres Of Computer Applications Provided By Ugc In Different Universities. * Meets The Requirements Of Students Of Physics At Undergraduate And Post-Graduate Level In Particular And Physical Sciences, Engineering And Mathematics Students In General.This Book Is An Outcome Of A Book Project Granted By University Grants Commission New Delhi (India). |
an introduction to computational physics: Introduction to Computational Physics Marvin L. De Jong, 1991 |
an introduction to computational physics: An Introduction to Computational Physics Sauro Succi, 2002 |
an introduction to computational physics: Computational Physics - A Practical Introduction to Computational Physics and Scientific Computing (using C++), Vol. II Konstantinos Anagnostopoulos, 2016-12-06 This book is an introduction to the computational methods used in physics, but also in 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. It assumes no prior knowledge of numerical analysis, programming or computers and teaches whatever is necessary for the solution of the problems addressed in the text. It can be used as a textbook in introductory computational physics or scientific computing classes. 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. All the material can be taught in two semesters, but a selection of topics can form the material of a one semester course. 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. It puts emphasis on hands--on programming of numerical code but also on the production, analysis and interpretation of data. 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. There is a C++ and a Fortran edition for the core programming. Data analysis is performed using the powerful tools of the GNU/Linux environment. All the necessary software is open source and freely available. The book and the accompanying software are given under a Creative Commons License/GNU public License as a service to the community. It can be used freely as a whole, or any part of it, in any form, by anyone. There is no official distribution of hard copies, but you can use the printing service of your preference in order produce any number of copies you need for you and/or your students. For the lazy ones, a very nice and cheap paperback can be purchaced from lulu.com, amazon.com and conventional bookstores. The ebook can be read in most electronic devices like your PC, tablet or favorite ebook reader and it is freely available from the book's website. |
an introduction to computational physics: Computational Physics Rubin H. Landau, Manuel J. Páez, Cristian C. Bordeianu, 2015-09-08 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). |
an introduction to computational physics: Computational Physics Franz J. Vesely, 2013-04-18 Author Franz J. Vesely offers students an introductory text on computational physics, providing them with the important basic numerical/computational techniques. His unique text sets itself apart from others by focusing on specific problems of computational physics. The author also provides a selection of modern fields of research. Students will benefit from the appendixes which offer a short description of some properties of computing and machines and outline the technique of 'Fast Fourier Transformation.' |
an introduction to computational physics: Computational Methods in Physics, Chemistry and Biology Paul Harrison, 2001-11-28 Eine gut verständliche Einführung in moderne naturwissenschaftliche Rechenmethoden! Nur geringe physikalische Vorkenntnisse voraussetzend, vermittelt der Autor Grundlagen und komplexere Ansätze anhand vieler Beispiele und ausgesprochen praxisnaher Übungsaufgaben. Besprochen werden alle Rechenmethoden, die im Grundstudium erlernt werden sollen, hinsichtlich ihrer Leistungsfähigkeit und ihrer Anwendungsgebiete. |
an introduction to computational physics: A First Course in Computational Physics Paul DeVries, Paul L. DeVries, Javier Hasbun, 2011-01-28 Computers and computation are extremely important components of physics and should be integral parts of a physicist’s education. Furthermore, computational physics is reshaping the way calculations are made in all areas of physics. Intended for the physics and engineering students who have completed the introductory physics course, A First Course in Computational Physics, Second Edition covers the different types of computational problems using MATLAB with exercises developed around problems of physical interest. Topics such as root finding, Newton-Cotes integration, and ordinary differential equations are included and presented in the context of physics problems. A few topics rarely seen at this level such as computerized tomography, are also included. Within each chapter, the student is led from relatively elementary problems and simple numerical approaches through derivations of more complex and sophisticated methods, often culminating in the solution to problems of significant difficulty. The goal is to demonstrate how numerical methods are used to solve the problems that physicists face. Read the review published in Computing in Science & Engineering magazine, March/April 2011 (Vol. 13, No. 2) ? 2011 IEEE, Published by the IEEE Computer Society |
an introduction to computational physics: Computational Physics Mark E. J. Newman, 2013 This book explains the fundamentals of computational physics and describes the techniques that every physicist should know, such as finite difference methods, numerical quadrature, and the fast Fourier transform. The book offers a complete introduction to the topic at the undergraduate level, and is also suitable for the advanced student or researcher. The book begins with an introduction to Python, then moves on to a step-by-step description of the techniques of computational physics, with examples ranging from simple mechanics problems to complex calculations in quantum mechanics, electromagnetism, statistical mechanics, and more. |
an introduction to computational physics: Statistical and Thermal Physics Harvey Gould, Jan Tobochnik, 2021-09-14 A completely revised edition that combines a comprehensive coverage of statistical and thermal physics with enhanced computational tools, accessibility, and active learning activities to meet the needs of today's students and educators This revised and expanded edition of Statistical and Thermal Physics introduces students to the essential ideas and techniques used in many areas of contemporary physics. Ready-to-run programs help make the many abstract concepts concrete. The text requires only a background in introductory mechanics and some basic ideas of quantum theory, discussing material typically found in undergraduate texts as well as topics such as fluids, critical phenomena, and computational techniques, which serve as a natural bridge to graduate study. Completely revised to be more accessible to students Encourages active reading with guided problems tied to the text Updated open source programs available in Java, Python, and JavaScript Integrates Monte Carlo and molecular dynamics simulations and other numerical techniques Self-contained introductions to thermodynamics and probability, including Bayes' theorem A fuller discussion of magnetism and the Ising model than other undergraduate texts Treats ideal classical and quantum gases within a uniform framework Features a new chapter on transport coefficients and linear response theory Draws on findings from contemporary research Solutions manual (available only to instructors) |
an introduction to computational physics: Applied Computational Physics Joseph F. Boudreau, Eric Scott Swanson, 2018 A textbook that addresses a wide variety of problems in classical and quantum physics. Modern programming techniques are stressed throughout, along with the important topics of encapsulation, polymorphism, and object-oriented design. Scientific problems are physically motivated, solution strategies are developed, and explicit code is presented. |
an introduction to computational physics: Computational Methods in Plasma Physics Stephen Jardin, 2010-06-02 Assuming no prior knowledge of plasma physics or numerical methods, Computational Methods in Plasma Physics covers the computational mathematics and techniques needed to simulate magnetically confined plasmas in modern magnetic fusion experiments and future magnetic fusion reactors. Largely self-contained, the text presents the basic concepts neces |
an introduction to computational physics: An Introduction to Computer Simulation Methods Harvey Gould, Jan Tobochnik, 1988 |
an introduction to computational physics: Introduction to Numerical Programming Titus A. Beu, 2014-09-03 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. |
an introduction to computational physics: Basic Concepts in Computational Physics Benjamin A. Stickler, Ewald Schachinger, 2016-03-21 This new edition is a concise introduction to the basic methods of computational physics. Readers will discover the benefits of numerical methods for solving complex mathematical problems and for the direct simulation of physical processes. The book is divided into two main parts: Deterministic methods and stochastic methods in computational physics. Based on concrete problems, the first part discusses numerical differentiation and integration, as well as the treatment of ordinary differential equations. This is extended by a brief introduction to the numerics of partial differential equations. The second part deals with the generation of random numbers, summarizes the basics of stochastics, and subsequently introduces Monte-Carlo (MC) methods. Specific emphasis is on MARKOV chain MC algorithms. The final two chapters discuss data analysis and stochastic optimization. All this is again motivated and augmented by applications from physics. In addition, the book offers a number of appendices to provide the reader with information on topics not discussed in the main text. Numerous problems with worked-out solutions, chapter introductions and summaries, together with a clear and application-oriented style support the reader. Ready to use C++ codes are provided online. |
an introduction to computational physics: Introduction to Computational Science Angela B. Shiflet, George W. Shiflet, 2014-03-30 The essential introduction to computational science—now fully updated and expanded Computational science is an exciting new field at the intersection of the sciences, computer science, and mathematics because much scientific investigation now involves computing as well as theory and experiment. This textbook provides students with a versatile and accessible introduction to the subject. It assumes only a background in high school algebra, enables instructors to follow tailored pathways through the material, and is the only textbook of its kind designed specifically for an introductory course in the computational science and engineering curriculum. While the text itself is generic, an accompanying website offers tutorials and files in a variety of software packages. This fully updated and expanded edition features two new chapters on agent-based simulations and modeling with matrices, ten new project modules, and an additional module on diffusion. Besides increased treatment of high-performance computing and its applications, the book also includes additional quick review questions with answers, exercises, and individual and team projects. The only introductory textbook of its kind—now fully updated and expanded Features two new chapters on agent-based simulations and modeling with matrices Increased coverage of high-performance computing and its applications Includes additional modules, review questions, exercises, and projects An online instructor's manual with exercise answers, selected project solutions, and a test bank and solutions (available only to professors) An online illustration package is available to professors |
an introduction to computational physics: Computational Methods for Physics Joel Franklin, 2013-05-23 There is an increasing need for undergraduate students in physics to have a core set of computational tools. Most problems in physics benefit from numerical methods, and many of them resist analytical solution altogether. This textbook presents numerical techniques for solving familiar physical problems where a complete solution is inaccessible using traditional mathematical methods. The numerical techniques for solving the problems are clearly laid out, with a focus on the logic and applicability of the method. The same problems are revisited multiple times using different numerical techniques, so readers can easily compare the methods. The book features over 250 end-of-chapter exercises. A website hosted by the author features a complete set of programs used to generate the examples and figures, which can be used as a starting point for further investigation. A link to this can be found at www.cambridge.org/9781107034303. |
an introduction to computational physics: Nanocomputing Jang-Yu Hsu, 2017-03-03 This book provides a comprehensive overview of the computational physics for nanoscience and nanotechnology. Based on MATLAB and the C++ distributed computing paradigm, the book gives instructive explanations of the underlying physics for mesoscopic systems with many listed programs that readily compute physical properties into nanoscales. Many generated graphical pictures demonstrate not only the principles of physics, but also the methodology of computing. |
an introduction to computational physics: Computational Physics Philipp Scherer, 2013-07-17 This textbook presents basic and advanced computational physics in a very didactic style. It contains very-well-presented and simple mathematical descriptions of many of the most important algorithms used in computational physics. The first part of the book discusses the basic numerical methods. The second part concentrates on simulation of classical and quantum systems. Several classes of integration methods are discussed including not only the standard Euler and Runge Kutta method but also multi-step methods and the class of Verlet methods, which is introduced by studying the motion in Liouville space. A general chapter on the numerical treatment of differential equations provides methods of finite differences, finite volumes, finite elements and boundary elements together with spectral methods and weighted residual based methods. The book gives simple but non trivial examples from a broad range of physical topics trying to give the reader insight into not only the numerical treatment but also simulated problems. Different methods are compared with regard to their stability and efficiency. The exercises in the book are realised as computer experiments. |
an introduction to computational physics: Introduction to Python for Science and Engineering David J. Pine, 2024-09-23 Introduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and “bottom up,” which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed. Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical integration, solutions to differential equations, and fast Fourier transforms. Readers learn how to interact and program with Python using JupyterLab and Spyder, two simple and widely used integrated development environments. All the major Python libraries for science and engineering are covered, including NumPy, SciPy, Matplotlib, and Pandas. Other packages are also introduced, including Numba, which can render Python numerical calculations as fast as compiled computer languages such as C but without their complex overhead. |
an introduction to computational physics: A First Course in Computational Physics and Object-Oriented Programming with C++ Hardback with CD-ROM David Yevick, 2005-03-17 Textbook and reference work on the application of C++ in science and engineering. |
an introduction to computational physics: Introduction to Computational Materials Science Richard LeSar, 2013-03-28 Emphasising essential methods and universal principles, this textbook provides everything students need to understand the basics of simulating materials behaviour. All the key topics are covered from electronic structure methods to microstructural evolution, appendices provide crucial background material, and a wealth of practical resources are available online to complete the teaching package. Modelling is examined at a broad range of scales, from the atomic to the mesoscale, providing students with a solid foundation for future study and research. Detailed, accessible explanations of the fundamental equations underpinning materials modelling are presented, including a full chapter summarising essential mathematical background. Extensive appendices, including essential background on classical and quantum mechanics, electrostatics, statistical thermodynamics and linear elasticity, provide the background necessary to fully engage with the fundamentals of computational modelling. Exercises, worked examples, computer codes and discussions of practical implementations methods are all provided online giving students the hands-on experience they need. |
an introduction to computational physics: Computational Physics R. C. Verma, R. K. Ahluwalia, K. C. Sharma, 1999 |
an introduction to computational physics: Computational Physics - A Practical Introduction to Computational Physics and Scientific Computing (using C++), Vol. I Konstantinos Anagnostopoulos, 2016-12-06 This book is an introduction to the computational methods used in physics and other related 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. It assumes no prior knowledge of numerical analysis, programming or computers and teaches whatever is necessary for the solution of the problems addressed in the text. C++ is used for programming the core programs and data analysis is performed using the powerful tools of the GNU/Linux environment. All the necessary software is open source and freely available. 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. |
an introduction to computational physics: Computational Physics of Carbon Nanotubes Hashem Rafii-Tabar, 2008 This book presents the key theories, computational modelling and numerical simulation tools required to understand carbon nanotube physics. Specifically, methods applied to geometry and bonding, mechanical, thermal, transport and storage properties are addressed. This self-contained book will interest researchers across a broad range of disciplines. |
an introduction to computational physics: Information, Physics, and Computation Marc Mézard, Andrea Montanari, 2009-01-22 A very active field of research is emerging at the frontier of statistical physics, theoretical computer science/discrete mathematics, and coding/information theory. This book sets up a common language and pool of concepts, accessible to students and researchers from each of these fields. |
an introduction to computational physics: Computational Physics Michael Bestehorn, 2018-04-09 Drawing on examples from various areas of physics, this textbook introduces the reader to computer-based physics using Fortran® and Matlab®. It elucidates a broad palette of topics, including fundamental phenomena in classical and quantum mechanics, hydrodynamics and dynamical systems, as well as effects in field theories and macroscopic pattern formation described by (nonlinear) partial differential equations. A chapter on Monte Carlo methods is devoted to problems typically occurring in statistical physics. Contents Introduction Nonlinear maps Dynamical systems Ordinary differential equations I Ordinary differential equations II Partial differential equations I, basics Partial differential equations II, applications Monte Carlo methods (MC) Matrices and systems of linear equations Program library Solutions of the problems README and a short guide to FE-tools |
an introduction to computational physics: Computational Many-Particle Physics Holger Fehske, Ralf Schneider, Alexander Weiße, 2007-12-10 Looking for the real state of play in computational many-particle physics? Look no further. This book presents an overview of state-of-the-art numerical methods for studying interacting classical and quantum many-particle systems. A broad range of techniques and algorithms are covered, and emphasis is placed on their implementation on modern high-performance computers. This excellent book comes complete with online files and updates allowing readers to stay right up to date. |
an introduction to computational physics: Numerical Methods in Physics with Python Alex Gezerlis, 2023-07-31 A standalone text on computational physics combining idiomatic Python, foundational numerical methods, and physics applications. |
an introduction to computational physics: Computational Physics Jos Thijssen, 2007-03-22 First published in 2007, this second edition is for graduate students and researchers in theoretical, computational and experimental physics. |
an introduction to computational physics: Computational Physics Karl H. Hoffmann, Michael Schreiber, 2012-12-06 Computational Physics. Selected Methods, Simple Exercises, Serious Applications is an overview written by leading researchers of a variety of fields and developments. Selected Methods introduce the reader to current fields, including molecular dynamics, hybrid Monte-Carlo algorithms, and neural networks. Simple Exercises give hands-on advice for effective program solutions from a small number of lines to demonstration programs with elaborate graphics. Serious Applications show how questions concerning, for example, aging, many-minima optimisation, or phase transitions can be treated by appropriate tools. The source code and demonstration graphics are included on a 3.5 MS-DOS diskette. |
an introduction to computational physics: Computational Approaches in Physics Maria Fyta, 2016-11-01 Computational Approaches in Physics reviews computational schemes which are used in the simulations of physical systems. These range from very accurate ab initio techniques up to coarse-grained and mesoscopic schemes. The choice of the method is based on the desired accuracy and computational efficiency. A bottom-up approach is used to present the various simulation methods used in Physics, starting from the lower level and the most accurate methods, up to particle-based ones. The book outlines the basic theory underlying each technique and its complexity, addresses the computational implications and issues in the implementation, as well as present representative examples. A link to the most common computational codes, commercial or open source is listed in each chapter. The strengths and deficiencies of the variety of techniques discussed in this book are presented in detail and visualization tools commonly used to make the simulation data more comprehensive are also discussed. In the end, specific techniques are used as bridges across different disciplines. To this end, examples of different systems tackled with the same methods are presented. The appendices include elements of physical theory which are prerequisites in understanding the simulation methods. |
an introduction to computational physics: Effective Computation in Physics Anthony Scopatz, Kathryn D. Huff, 2015-06-25 More physicists today are taking on the role of software developer as part of their research, but software development isnâ??t always easy or obvious, even for physicists. This practical book teaches essential software development skills to help you automate and accomplish nearly any aspect of research in a physics-based field. Written by two PhDs in nuclear engineering, this book includes practical examples drawn from a working knowledge of physics concepts. Youâ??ll learn how to use the Python programming language to perform everything from collecting and analyzing data to building software and publishing your results. In four parts, this book includes: Getting Started: Jump into Python, the command line, data containers, functions, flow control and logic, and classes and objects Getting It Done: Learn about regular expressions, analysis and visualization, NumPy, storing data in files and HDF5, important data structures in physics, computing in parallel, and deploying software Getting It Right: Build pipelines and software, learn to use local and remote version control, and debug and test your code Getting It Out There: Document your code, process and publish your findings, and collaborate efficiently; dive into software licenses, ownership, and copyright procedures |
an introduction to computational physics: Computational Problems for Physics Rubin H. Landau, Manuel José Páez, 2018-05-30 Our future scientists and professionals must be conversant in computational techniques. In order to facilitate integration of computer methods into existing physics courses, this textbook offers a large number of worked examples and problems with fully guided solutions in Python as well as other languages (Mathematica, Java, C, Fortran, and Maple). It’s also intended as a self-study guide for learning how to use computer methods in physics. The authors include an introductory chapter on numerical tools and indication of computational and physics difficulty level for each problem. Readers also benefit from the following features: • Detailed explanations and solutions in various coding languages. • Problems are ranked based on computational and physics difficulty. • Basics of numerical methods covered in an introductory chapter. • Programming guidance via flowcharts and pseudocode. Rubin Landau is a Distinguished Professor Emeritus in the Department of Physics at Oregon State University in Corvallis and a Fellow of the American Physical Society (Division of Computational Physics). Manuel Jose Paez-Mejia is a Professor of Physics at Universidad de Antioquia in Medellín, Colombia. |
an introduction to computational physics: An introduction to computational physics Sauro Succi, 2002-10-01 These volumes collect the lecture notes of the course “An introduction to computational physics” held in the academic year 2000/01 for students of the University of Pisa and Scuola Normale Superiore at the level of the last two-year undergraduates in physics and chemistry. Grid methods are the tool of the trade for the solution of ordinary and partial differential equations and consequently they represent a “must” for anyone dealing with computational science. With grid methods, a major distinction is made between methods which do not require matrix algebra and those which do. |
an introduction to computational physics: An Introduction to Scientific Computing Ionut Danaila, Pascal Joly, Sidi Mahmoud Kaber, Marie Postel, 2007-12-03 This book demonstrates scientific computing by presenting twelve computational projects in several disciplines including Fluid Mechanics, Thermal Science, Computer Aided Design, Signal Processing and more. Each follows typical steps of scientific computing, from physical and mathematical description, to numerical formulation and programming and critical discussion of results. The text teaches practical methods not usually available in basic textbooks: numerical checking of accuracy, choice of boundary conditions, effective solving of linear systems, comparison to exact solutions and more. The final section of each project contains the solutions to proposed exercises and guides the reader in using the MATLAB scripts available online. |
INTRODUCTION Definition & Meaning - Merriam-Webster
The meaning of INTRODUCTION is something that introduces. How to use introduction in a sentence.
How to Write an Introduction, With Examples | Grammarly
Oct 20, 2022 · An introduction should include three things: a hook to interest the reader, some background on the topic so the reader can understand it, and a thesis statement that clearly and …
INTRODUCTION | English meaning - Cambridge Dictionary
INTRODUCTION definition: 1. an occasion when something is put into use or brought to a place for the first time: 2. the act…. Learn more.
INTRODUCTION Definition & Meaning | Dictionary.com
What is an introduction? The introduction is the first section of an essay. It presents, or introduces, the essay topic and includes a thesis statement. Students are usually taught to write an essay in …
What Is an Introduction? Definition & 25+ Examples - Enlightio
Nov 5, 2023 · An introduction is the initial section of a piece of writing, speech, or presentation wherein the author presents the topic and purpose of the material. It serves as a gateway for the …