9783319801032 - basic concepts in computational physics de stickler, benjamin a.; schachinger, ewald (17 resultados)
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Paperback. Condición: new. Paperback. 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: Determinis…tic 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. Inaddition, 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Condición: New. pp. 425.
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Editorial: Springer International Publishing, Springer International Publishing, 2018
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This new edition is a concise introduction to the basic methods of computational physics. Readerswill discover the benefits of numerical methods for solving complex mathematical problems and for thedirect simulation of physical processes. The book…is divided into two main parts: Deterministic methods and stochastic methods in computationalphysics. 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 thenumerics 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. Specificemphasis is on MARKOV chain MC algorithms. The final two chapters discuss data analysis and stochasticoptimization. All this is again motivated and augmented by applications from physics. Inaddition, the bookoffers 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 clearand application-oriented style support the reader. Ready to use C++ codes are provided online.
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Taschenbuch. Condición: Neu. Basic Concepts in Computational Physics | Benjamin A. Stickler (u. a.) | Taschenbuch | xvi | Englisch | 2018 | Springer | EAN 9783319801032 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Paperback. Condición: new. Paperback. 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: Determinis…tic 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. Inaddition, 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Paperback. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Condición: new. Questo è un articolo print on demand.
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Paperback. Condición: Brand New. 2nd reprint edition. 425 pages. 9.25x6.10x1.18 inches. In Stock. This item is printed on demand.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 pr…ocesses.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. 428 pp. Englisch.
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Condición: New. Print on Demand pp. 425.
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Condición: New. PRINT ON DEMAND pp. 425.
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Now with ready to use C++ program code available online Contains heavily expanded chapters on molecular dynamics, PDEs, random generators, Monte Carlo applications, data analysis and data optimization Presents determi…nistic methods are pres.
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 proces…ses.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. Inaddition, 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 428 pp. Englisch.
