Rubin H. Landau – författare
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6 produkter
6 produkter
2 297 kr
Kommande
Our future scientists and professionals must be conversant in computational techniques. In order to facilitate integration of computer methods into existing physics courses, Computational Problems for Physics offers a large number of worked examples and problems with fully guided solutions in Python (as well as Mathematica, Java, C, Fortran, and Maple on the Web). The book can be used as a self-study guide for learning how to use computer methods in physics. Fully revised, this second edition includes:A chapter on neural networks, machine learning, and artificial intelligence, with the building of simple networks, and the use of machine learning software.A chapter on quantum computing with some problems to be run on the IBM Quantum Computer.A chapter on general relativity with manipulations of the field equations and with computation of GR corrections to classical mechanics.An expanded coverage of principal component analysis.A crucial resource for students beginning their study of computational physics with in-depth and engaging problems and exercises.
873 kr
Kommande
Our future scientists and professionals must be conversant in computational techniques. In order to facilitate integration of computer methods into existing physics courses, Computational Problems for Physics offers a large number of worked examples and problems with fully guided solutions in Python (as well as Mathematica, Java, C, Fortran, and Maple on the Web). The book can be used as a self-study guide for learning how to use computer methods in physics. Fully revised, this second edition includes:A chapter on neural networks, machine learning, and artificial intelligence, with the building of simple networks, and the use of machine learning software.A chapter on quantum computing with some problems to be run on the IBM Quantum Computer.A chapter on general relativity with manipulations of the field equations and with computation of GR corrections to classical mechanics.An expanded coverage of principal component analysis.A crucial resource for students beginning their study of computational physics with in-depth and engaging problems and exercises.
1 086 kr
Skickas inom 10-15 vardagar
Our future scientists and professionals must be conversant in computational techniques. In order to facilitate integration of computer methods into existing physics courses, this textbook offers a large number of worked examples and problems with fully guided solutions in Python as well as other languages (Mathematica, Java, C, Fortran, and Maple). It’s also intended as a self-study guide for learning how to use computer methods in physics. The authors include an introductory chapter on numerical tools and indication of computational and physics difficulty level for each problem. Readers also benefit from the following features:• Detailed explanations and solutions in various coding languages.• Problems are ranked based on computational and physics difficulty.• Basics of numerical methods covered in an introductory chapter.• Programming guidance via flowcharts and pseudocode.Rubin Landau is a Distinguished Professor Emeritus in the Department of Physics at Oregon State University in Corvallis and a Fellow of the American Physical Society (Division of Computational Physics).Manuel Jose Paez-Mejia is a Professor of Physics at Universidad de Antioquia in Medellín, Colombia.
1 715 kr
Skickas inom 10-15 vardagar
Our future scientists and professionals must be conversant in computational techniques. In order to facilitate integration of computer methods into existing physics courses, this textbook offers a large number of worked examples and problems with fully guided solutions in Python as well as other languages (Mathematica, Java, C, Fortran, and Maple). It’s also intended as a self-study guide for learning how to use computer methods in physics. The authors include an introductory chapter on numerical tools and indication of computational and physics difficulty level for each problem. Readers also benefit from the following features:• Detailed explanations and solutions in various coding languages.• Problems are ranked based on computational and physics difficulty.• Basics of numerical methods covered in an introductory chapter.• Programming guidance via flowcharts and pseudocode.Rubin Landau is a Distinguished Professor Emeritus in the Department of Physics at Oregon State University in Corvallis and a Fellow of the American Physical Society (Division of Computational Physics).Manuel Jose Paez-Mejia is a Professor of Physics at Universidad de Antioquia in Medellín, Colombia.
1 030 kr
Tillfälligt slut
1 105 kr
Skickas
The classic in the field for more than 25 years, now with increased emphasis on data science and new chapters on quantum computing, machine learning (AI), and general relativityComputational physics combines physics, applied mathematics, and computer science in a cutting-edge multidisciplinary approach to solving realistic physical problems. It has become integral to modern physics research because of its capacity to bridge the gap between mathematical theory and real-world system behavior. Computational Physics provides the reader with the essential knowledge to understand computational tools and mathematical methods well enough to be successful. Its philosophy is rooted in “learning by doing”, assisted by many sample programs in the popular Python programming language. The first third of the book lays the fundamentals of scientific computing, including programming basics, stable algorithms for differentiation and integration, and matrix computing. The latter two-thirds of the textbook cover more advanced topics such linear and nonlinear differential equations, chaos and fractals, Fourier analysis, nonlinear dynamics, and finite difference and finite elements methods. A particular focus in on the applications of these methods for solving realistic physical problems. Readers of the fourth edition of Computational Physics will also find: An exceptionally broad range of topics, from simple matrix manipulations to intricate computations in nonlinear dynamicsA whole suite of supplementary material: Python programs, Jupyter notebooks and videosComputational Physics is ideal for students in physics, engineering, materials science, and any subjects drawing on applied physics.