Sprache: Englisch
Verlag: Cambridge University Press, 2023
ISBN 10: 1009303864 ISBN 13: 9781009303866
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paperback. Zustand: Very Good.
Sprache: Englisch
Verlag: Cambridge University Press, 2023
ISBN 10: 1009303856 ISBN 13: 9781009303859
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hardcover. Zustand: Very Good.
Sprache: Englisch
Verlag: Cambridge University Press, 2023
ISBN 10: 1009303864 ISBN 13: 9781009303866
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In den WarenkorbZustand: New. In.
Sprache: Englisch
Verlag: Cambridge University Press, 2020
ISBN 10: 1108738931 ISBN 13: 9781108738934
Anbieter: Books From California, Simi Valley, CA, USA
paperback. Zustand: Very Good. Cover and edges may have some wear.
Sprache: Englisch
Verlag: Cambridge University Press, 2023
ISBN 10: 1009303864 ISBN 13: 9781009303866
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Zustand: New. 2023. 2nd Edition. Paperback. . . . . . Books ship from the US and Ireland.
Sprache: Englisch
Verlag: Cambridge University Press, 2023
ISBN 10: 1009303864 ISBN 13: 9781009303866
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In den WarenkorbPaperback. Zustand: Brand New. 2nd edition. 700 pages. 10.00x7.00x1.41 inches. In Stock.
Sprache: Englisch
Verlag: Cambridge University Press, 2023
ISBN 10: 1009303864 ISBN 13: 9781009303866
Anbieter: moluna, Greven, Deutschland
Zustand: New. Über 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.
Sprache: Englisch
Verlag: Cambridge University Press Jul 2023, 2023
ISBN 10: 1009303864 ISBN 13: 9781009303866
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: 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.
Sprache: Englisch
Verlag: Cambridge University Press, 2023
ISBN 10: 1009303864 ISBN 13: 9781009303866
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Numerical Methods in Physics with Python | Alex Gezerlis | Taschenbuch | Kartoniert / Broschiert | Englisch | 2023 | Cambridge University Press | EAN 9781009303866 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Sprache: Englisch
Verlag: Cambridge University Press, 2023
ISBN 10: 1009303856 ISBN 13: 9781009303859
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbHardcover. Zustand: Brand New. 2nd edition. 700 pages. 10.00x7.00x1.50 inches. In Stock.
Sprache: Englisch
Verlag: Cambridge University Press Jul 2023, 2023
ISBN 10: 1009303856 ISBN 13: 9781009303859
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: 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.