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Computation in science
Title statement Computation in science / Konrad Hinsen. [elektronický zdroj] Publication San Rafael [California] (40 Oak Drive, San Rafael, CA, 94903, USA) : Morgan & Claypool Publishers, [2015] Distribution Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2015] Phys.des. 1 online resource (various pagings) : illustrations (some color). ISBN 9781681740935 (online) 9781681742212 mobi Edition [IOP release 2] IOP concise physics, ISSN 2053-2571 Note "Version: 20151201"--Title page verso. "A Morgan & Claypool publication as part of IOP Concise Physics"--Title page verso. Internal Bibliographies/Indexes Note Includes bibliographical references. Contents Preface -- 1. What is computation? -- 1.1. Defining computation -- 1.2. The roles of computation in scientific research -- 1.3. Further reading Content note 2. Computation in science -- 2.1. Traditional science : celestial mechanics -- 2.2. Scientific models and computation -- 2.3. Computation at the interface between observations and models -- 2.4. Computation for developing insight -- 2.5. The impact of computing on science -- 2.6. Further reading. 3. Formalizing computation -- 3.1. From manual computation to rewriting rules -- 3.2. From computing machines to automata theory -- 3.3. Computability -- 3.4. Restricted models of computation -- 3.5. Computational complexity -- 3.6. Computing with numbers -- 3.7. Further reading. 4. Automating computation -- 4.1. Computer architectures -- 4.2. Programming languages -- 4.3. Software engineering -- 4.4. Further reading. 5. Taming complexity -- 5.1. Chaos and complexity in computation -- 5.2. Validation and testing -- 5.3. Abstraction -- 5.4. Managing state -- 5.5. Incidental complexity and technical debt -- 5.6. Further reading. 6. Outlook : scientific knowledge in the digital age -- 6.1. Software as a medium for representing scientific knowledge -- 6.2. Reproducibility -- 6.3. The time scales of scientific progress and computing -- 6.4. Preparing the future -- 6.5. Further reading. Notes to Availability Přístup pouze pro oprávněné uživatele Audience Graduate and postgraduate professional researchers and engineers. Note Způsob přístupu: World Wide Web.. Požadavky na systém: Adobe Acrobat Reader. Another responsib. Morgan & Claypool Publishers, Institute of Physics (Great Britain), Subj. Headings Science - Mathematics. * SCIENCE / Physics / General. * Physics. Form, Genre elektronické knihy electronic books Country Kalifornie Language angličtina Document kind Electronic books URL Plný text pro studenty a zaměstnance UPOL 
book
Computation in Science provides a theoretical background in computation to scientists who use computational methods. It explains how computing is used in the natural sciences, and provides a high-level overview of those aspects of computer science and software engineering that are most relevant for computational science. The focus is on concepts, results, and applications, rather than on proofs and derivations. The unique feature of this book is that it connects the dots between computational science, the theory of computation and information, and software engineering. It should help scientists to better understand how they use computers in their work, and to how computers work. It is meant to compensate for the general lack of any formal training in computer science and information theory. Readers will learn something that they can use throughout their careers.
Preface -- 1. What is computation? -- 1.1. Defining computation -- 1.2. The roles of computation in scientific research -- 1.3. Further reading2. Computation in science -- 2.1. Traditional science : celestial mechanics -- 2.2. Scientific models and computation -- 2.3. Computation at the interface between observations and models -- 2.4. Computation for developing insight -- 2.5. The impact of computing on science -- 2.6. Further reading3. Formalizing computation -- 3.1. From manual computation to rewriting rules -- 3.2. From computing machines to automata theory -- 3.3. Computability -- 3.4. Restricted models of computation -- 3.5. Computational complexity -- 3.6. Computing with numbers -- 3.7. Further reading4. Automating computation -- 4.1. Computer architectures -- 4.2. Programming languages -- 4.3. Software engineering -- 4.4. Further reading5. Taming complexity -- 5.1. Chaos and complexity in computation -- 5.2. Validation and testing -- 5.3. Abstraction -- 5.4. Managing state -- 5.5. Incidental complexity and technical debt -- 5.6. Further reading6. Outlook : scientific knowledge in the digital age -- 6.1. Software as a medium for representing scientific knowledge -- 6.2. Reproducibility -- 6.3. The time scales of scientific progress and computing -- 6.4. Preparing the future -- 6.5. Further reading.
Number of the records: 1