Introduction to Computational Science

Author: Angela B. Shiflet
Publisher: Princeton University Press
ISBN: 140085055X
Format: PDF, Mobi
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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 Computational Science

Author: Angela B. Shiflet
Publisher: Princeton University Press
ISBN: 1400841119
Format: PDF, Kindle
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Computational science is a quickly emerging field at the intersection of the sciences, computer science, and mathematics because much scientific investigation now involves computing as well as theory and experiment. However, limited educational materials exist in this field. Introduction to Computational Science fills this void with a flexible, readable textbook that assumes only a background in high school algebra and enables instructors to follow tailored pathways through the material. It is the first textbook designed specifically for an introductory course in the computational science and engineering curriculum. The text embraces two major approaches to computational science problems: System dynamics models with their global views of major systems that change with time; and cellular automaton simulations with their local views of how individuals affect individuals. While the text is generic, an extensive author-generated Web-site contains tutorials and files in a variety of software packages to accompany the text. Generic software approach in the text Web site with tutorials and files in a variety of software packages Engaging examples, exercises, and projects that explore science Additional, substantial projects for students to develop individually or in teams Consistent application of the modeling process Quick review questions and answers Projects for students to develop individually or in teams Reference sections for most modules, as well as a glossary Online instructor's manual with a test bank and solutions

Introduction to Computational Science

Author: Angela B. Shiflet
Publisher: Princeton University Press
ISBN: 0691125651
Format: PDF, Docs
Download Now
Computational science is a quickly emerging field at the intersection of the sciences, computer science, and mathematics because much scientific investigation now involves computing as well as theory and experiment. However, limited educational materials exist in this field. Introduction to Computational Science fills this void with a flexible, readable textbook that assumes only a background in high school algebra and enables instructors to follow tailored pathways through the material. It is the first textbook designed specifically for an introductory course in the computational science and engineering curriculum. The text embraces two major approaches to computational science problems: System dynamics models with their global views of major systems that change with time; and cellular automaton simulations with their local views of how individuals affect individuals. While the text is generic, an extensive author-generated Web-site contains tutorials and files in a variety of software packages to accompany the text. Generic software approach in the text Web site with tutorials and files in a variety of software packages Engaging examples, exercises, and projects that explore science Additional, substantial projects for students to develop individually or in teams Consistent application of the modeling process Quick review questions and answers Projects for students to develop individually or in teams Reference sections for most modules, as well as a glossary Online instructor's manual with a test bank and solutions

Molecular Modeling and Simulation

Author: Tamar Schlick
Publisher: Springer Science & Business Media
ISBN: 0387224645
Format: PDF, ePub, Docs
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Very broad overview of the field intended for an interdisciplinary audience; Lively discussion of current challenges written in a colloquial style; Author is a rising star in this discipline; Suitably accessible for beginners and suitably rigorous for experts; Features extensive four-color illustrations; Appendices featuring homework assignments and reading lists complement the material in the main text

Simulation For The Social Scientist

Author: Gilbert, Nigel
Publisher: McGraw-Hill Education (UK)
ISBN: 9780335216000
Format: PDF, Docs
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Social sciences -- Simulation methods. Social interaction -- Computer simulation. Social sciences -- Mathematical models. (publisher)

Computer Simulation and Modelling

Author: Francis Neelamkavil
Publisher: John Wiley & Sons Incorporated
ISBN:
Format: PDF, Mobi
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This one-volume text covers all important aspects of computer modelling and simulation. Based on the idea of ``learning by doing,'' this text teaches the actual construction and use of both analogue and digital simulation models in continuous and discrete systems, while emphasizing the digital computer simulation of discrete systems. Covers the use of microprocessors and computer graphics for modelling and simulation and the availability of micro-based software. Stresses practical problem-solving with numerous diagrams and numerical examples. Also provided are sample program listings (Pascal, CSMP, GPSS, SIMSCRIPT) and output from actual computer runs.

A Primer on Scientific Programming with Python

Author: Hans Petter Langtangen
Publisher: Springer
ISBN: 3662498871
Format: PDF
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The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012 “This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” Joan Horvath, Computing Reviews, March 2015

Principles of Computational Modelling in Neuroscience

Author: David Sterratt
Publisher: Cambridge University Press
ISBN: 1139500791
Format: PDF, ePub, Mobi
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The nervous system is made up of a large number of interacting elements. To understand how such a complex system functions requires the construction and analysis of computational models at many different levels. This book provides a step-by-step account of how to model the neuron and neural circuitry to understand the nervous system at all levels, from ion channels to networks. Starting with a simple model of the neuron as an electrical circuit, gradually more details are added to include the effects of neuronal morphology, synapses, ion channels and intracellular signalling. The principle of abstraction is explained through chapters on simplifying models, and how simplified models can be used in networks. This theme is continued in a final chapter on modelling the development of the nervous system. Requiring an elementary background in neuroscience and some high school mathematics, this textbook is an ideal basis for a course on computational neuroscience.

Introduction to Computational Social Science

Author: Claudio Cioffi-Revilla
Publisher: Springer
ISBN: 3319501313
Format: PDF, ePub, Mobi
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This textbook provides a comprehensive and reader-friendly introduction to the field of computational social science (CSS). Presenting a unified treatment, the text examines in detail the four key methodological approaches of automated social information extraction, social network analysis, social complexity theory, and social simulation modeling. This updated new edition has been enhanced with numerous review questions and exercises to test what has been learned, deepen understanding through problem-solving, and to practice writing code to implement ideas. Topics and features: contains more than a thousand questions and exercises, together with a list of acronyms and a glossary; examines the similarities and differences between computers and social systems; presents a focus on automated information extraction; discusses the measurement, scientific laws, and generative theories of social complexity in CSS; reviews the methodology of social simulations, covering both variable- and object-oriented models.