- Tapa blanda: 634 páginas
- Editor: Cambridge University Press; Edición: 2 (10 de octubre de 2013)
- Idioma: Inglés
- ISBN-10: 1107677130
- ISBN-13: 978-1107677135
- Valoración media de los clientes: Sé el primero en opinar sobre este producto
- Clasificación en los más vendidos de Amazon: nº367.204 en Libros en idiomas extranjeros (Ver el Top 100 en Libros en idiomas extranjeros)
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Computational Physics (Inglés) Tapa blanda – 10 oct 2013
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Descripción del producto
'The growing importance of computational physics to physics research as a whole will depend not only on increasingly powerful computers, but also on the continuing development of algorithms and numerical techniques for putting these machines to use. Furthermore, physics departments will need to augment their curricula to provide students with the skills needed to perform research using computers … In Computational Physics, [Jos] Thijssen has produced a book that is well suited to meeting these needs … This book makes it easier to approach a new topic and encourages the reader to consider a modular approach when writing programs.' Physics Today
'… I find this book very useful since it provides a thorough discussion of the computational methods used in physics combined with an extensive presentation of the underlying physics … On the one hand an experienced researcher can easily transfer the obtained knowledge from this book to a particular research topic, while on the other hand a newcomer in the field will benefit from the presentation of the subject from first principles.' Lampros Nikolopoulos, Contemporary Physics
Reseña del editor
First published in 2007, this second edition describes the computational methods used in theoretical physics. New sections were added to cover finite element methods and lattice Boltzmann simulation, density functional theory, quantum molecular dynamics, Monte Carlo simulation, and diagonalisation of one-dimensional quantum systems. It covers many different areas of physics research and different computational methodologies, including computational methods such as Monte Carlo and molecular dynamics, various electronic structure methodologies, methods for solving partial differential equations, and lattice gauge theory. Throughout the book the relations between the methods used in different fields of physics are emphasised. Several new programs are described and can be downloaded from www.cambridge.org/9781107677135. The book requires a background in elementary programming, numerical analysis, and field theory, as well as undergraduate knowledge of condensed matter theory and statistical physics. It will be of interest to graduate students and researchers in theoretical, computational and experimental physics.Ver Descripción del producto
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The introduction states that this text is intended for graduate students in physics, chemistry, materials science, or electrical engineering, and who have taken classes in numerical analysis. I think a more appropriate wording is that this text is for someone versed in all of these listed fields. There is extensive use of thermodynamics, symmetry and crystal structure, linear algebra, statistical mechanics, quantum mechanics, etc... This book should not be used as an introductory guide to computational physics or related fields. The necessary prerequisite knowledge is quite extensive.
The intro should specify at least 2 college classes in computer programming as a prerequisite for this book. The programming assignments included at the end of each chapter are quite challenging, and should not be attempted by someone without previous experience in writing mathematical codes. This here lies another problem with the approach taken by this book. Most science and engineering majors will take 1-2 courses in programming as part of their university education, but these classes often emphasize business applications such as reading / writing to a text file, creating and using databases, formatting of screen output, linked lists, etc... These skills are not very useful in writing a code to do computations. For the latter, needed skills include parsing data, recognizing patterns, using built-in functions, importing and using algorithms from online libraries. utilizing large matrices and vectors, etc...
What the author should have done for each computational homework problem is to write out the solution (code) himself, add in the documentation, and then removed the code while leaving the documentation intact. The student can then use the documentation to craft his/her own solution.
For the difficulty of the computing problems, and of the text in general, I dock another star.
Therefore, I rate this book 3 out of 5 stars.