Introduction to Computational Science
Introduction to Computational Science

Author: Angela B. Shiflet

Publisher: Princeton University Press

Published: 2014-03-30

Total Pages: 857

ISBN-13: 140085055X

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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

Introduction to Computation in Physical Sciences
Introduction to Computation in Physical Sciences

Author: Jay Wang

Publisher: Springer Nature

Published: 2023-01-25

Total Pages: 264

ISBN-13: 3031176464

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This book provides a practical and comprehensive introduction to computational problem solving from the viewpoints of practitioners in both academic and industrial worlds. The authors present scientific problem-solving using computation and aim to increase computational thinking, which is the mindset and skillset required to solve scientific problems with computational methodologies via model building, simulation, data analysis, and visualization using the Python programming language. Topics and examples span fundamental areas of physical science as well as contemporary topics including quantum computing, neural networks, machine learning, global warming, and energy balance. The book features unique and innovative techniques and practices including: intentional scaffolding to help beginners learn computational problem solving; multimodal computing environments including cloud-based platforms and just-in-time computing; emphasis and connection between both numerical and symbolic computations; and extensive exercise sets carefully designed for further exploration as project assignments or self-paced study. The book is suitable for introductory level readers in physical sciences, engineering, and related STEM disciplines. Specifically, the book is appropriate for use in either a standalone course on computation and modeling and as a resource for readers interested in learning about proven techniques in interactive computing.

Information, Physics, and Computation
Information, Physics, and Computation

Author: Marc Mézard

Publisher: Oxford University Press

Published: 2009-01-22

Total Pages: 584

ISBN-13: 019857083X

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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.

Effective Computation in Physics
Effective Computation in Physics

Author: Anthony Scopatz

Publisher: "O'Reilly Media, Inc."

Published: 2015-06-25

Total Pages: 567

ISBN-13: 1491901586

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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

Introduction to Computation and Programming Using Python, second edition
Introduction to Computation and Programming Using Python, second edition

Author: John V. Guttag

Publisher: MIT Press

Published: 2016-08-12

Total Pages: 466

ISBN-13: 0262529629

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The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.

Introduction to Computational Materials Science
Introduction to Computational Materials Science

Author: Richard LeSar

Publisher: Cambridge University Press

Published: 2013-03-28

Total Pages: 429

ISBN-13: 1107328144

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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.

Introduction to High Performance Computing for Scientists and Engineers
Introduction to High Performance Computing for Scientists and Engineers

Author: Georg Hager

Publisher: CRC Press

Published: 2010-07-02

Total Pages: 350

ISBN-13: 1439811938

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Written by high performance computing (HPC) experts, Introduction to High Performance Computing for Scientists and Engineers provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC. From working in a scientific computing center, the author

Quantum Computing
Quantum Computing

Author: Eleanor G. Rieffel

Publisher: MIT Press

Published: 2011-03-04

Total Pages: 389

ISBN-13: 0262015064

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A thorough exposition of quantum computing and the underlying concepts of quantum physics, with explanations of the relevant mathematics and numerous examples.

Computational Physics
Computational Physics

Author: Rubin H. Landau

Publisher: John Wiley & Sons

Published: 2015-09-08

Total Pages: 647

ISBN-13: 3527413154

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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).