Computational Physics Problem Solving With Computers

Sometimes, the numerical results defy out intuition, and make us reshape our understanding of the problem.This is the case of "chaos", for instance, where the dynamics of simple classical systems gives rise to some surprising behavior.The use of computation and simulation has become an essential part of the scientific process.

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Some movies created by simulations are encapsulated into the text in order to produce live figures.

Furthermore, the equations in the e Text are in Math ML, and so can be imported into symbolic manipulation systems such as Maple and Mathematica.

Python has become very popular, particularly for physics education and large scientific projects.

It is probably the easiest programming language to learn for beginners, yet is also used for mainstream scientific computing, and has packages for excellent graphics and even symbolic manipulations.

The text is designed for an upper-level undergraduate or beginning graduate course and provides the reader with the essential knowledge to understand computational tools and mathematical methods well enough to be successful.

As part of the teaching of using computers to solve scientific problems, the reader is encouraged to work through a sample problem stated at the beginning of each chapter or unit, which involves studying the text, writing, debugging and running programs, visualizing the results, and the expressing in words what has been done and what can be concluded.I am assuming knowledge of Numerical Analysis, and some programming language, including how to use compilers. This is not a programming or C course, though, so students are welcome to use another language of choice.However, I am going to teach how to implement numerical algorithms to solve physical problems, and how to optimize them to make them more efficient.The fundamental advantage of using computers in physics is the ability to treat systems that cannot be solved analytically.In the usual situation we can gain insight on the physics of a problem studying soluble models, or limits of a problem that can be treated exactly.Therefore, it will also serve as a complementary condensed matter course.The course will be mostly based on this book: Not all topics will be included in the book.This upper-division text provides an unusually broad survey of the topics of modern computational physics from a multidisciplinary, computational science point of view.Its philosophy is rooted in learning by doing (assisted by many model programs), with new scientific materials as well as with the Python programming language.If you own the copyright to this book and it is wrongfully on our website, we offer a simple DMCA procedure to remove your content from our site. About the Subject Matter This upper-division text surveys most modern computational physics subjects from a computational science point of view that emphasises how mathematics and computer science as well physics are used together to solve problems.


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