Isbn: 9781009303859 - numerical methods in physics with python (13 resultados)

hardcover. Condición: Very Good. Cover and edges may have some wear.

Condición: As New. Unread book in perfect condition.

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Condición: New.

Condición: As New. Unread book in perfect condition.

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Condición: New. &Uumlber den AutorAlex Gezerlis is Professor of Physics at the University of Guelph. Before moving to Canada, he worked in Germany, the United States, and Greece. He has received several research awards, grants, and allocations on super.

Condición: New. 2nd edition NO-PA16APR2015-KAP.

Hardcover. Condición: Brand New. 2nd edition. 700 pages. 10.00x7.00x1.50 inches. In Stock.

Buch. Condición: Neu. Neuware - Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. The second edition of this introductory book features several new codes and 140 new problems (many on physics applications), as well as new sections on the singular-value decomposition, derivative-free optimization, Bayesian linear regression, neural networks, and partial differential equations. The last section in each chapter is an in-depth project, tackling physics problems that cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the numerical methods often used in the subject.…

Hardcover. Condición: new. Hardcover. Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. The second edition of this introductory book features several new codes and 140 new problems (many on physics applications), as well as new sections on the singular-value decomposition, derivative-free optimization, Bayesian linear regression, neural networks, and partial differential equations. The last section in each chapter is an in-depth project, tackling physics problems that cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the numerical methods often used in the subject. Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this book covers linear algebra, differential equations, root-finding, interpolation, and integration. Fully implementing many numerical methods in Python and with 140 new problems, it is an ideal standalone textbook on computational physics. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

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