9783527414253 - Computational Physics: Problem Solving with Python de Landau, Rubin H.; Paacute;ez, Manuel J.; Bordeianu, Cristian C. (35 resultados)

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Paperback. Condición: new. Paperback. 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 relativity Computational 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 videos Computational Physics is ideal for students in physics, engineering, materials science, and any subjects drawing on applied physics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condición: New.

Condición: New.

Paperback. Condición: New. 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 relativity Computational 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 videos Computational Physics is ideal for students in physics, engineering, materials science, and any subjects drawing on applied physics.

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Condición: New. 2024. 4th Edition. paperback. . . . . .

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Paperback. Condición: New. 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 relativity Computational 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 videos Computational Physics is ideal for students in physics, engineering, materials science, and any subjects drawing on applied physics.

Condición: New. 4th edition NO-PA16APR2015-KAP.

Taschenbuch. Condición: Neu. Neuware -Fourth edition of a classic on computational physics with new chapters on data science, machine learning and general relativity, plus a plethora of supplementary materials. 592 pp. Englisch.

Taschenbuch. Condición: Neu. Neuware -Fourth edition of a classic on computational physics with new chapters on data science, machine learning and general relativity, plus a plethora of supplementary materials. 592 pp. Englisch.

Taschenbuch. Condición: Neu. Neuware -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 relativity Computational 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 dynamics- A whole suite of supplementary material: Python programs, Jupyter not Elektronisches Buch and videos Computational Physics is ideal for students in physics, engineering, materials science, and any subjects drawing on applied physics.

Condición: New. 2024. 4th Edition. paperback. . . . . . Books ship from the US and Ireland.

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Condición: New. Rubin H. Landau is Professor Emeritus in the Department of Physics at Oregon State University in Corvallis. He has been teaching courses in computational physics for over 25 years, was a founder of the Computational Physics Degree Program and the Northwest .

Taschenbuch. Condición: Neu. Computational Physics | Problem Solving with Python | Rubin H. Landau (u. a.) | Taschenbuch | 592 S. | Englisch | 2024 | Wiley-VCH GmbH | EAN 9783527414253 | Verantwortliche Person für die EU: Wiley-VCH GmbH, Boschstr. 12, 69469 Weinheim, product-safety[at]wiley[dot]com | Anbieter: preigu.

Paperback. Condición: New. 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 relativity Computational 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 videos Computational Physics is ideal for students in physics, engineering, materials science, and any subjects drawing on applied physics.

Taschenbuch. Condición: Neu. Neuware -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 relativityWiley-VCH GmbH, Boschstraße 12, 69469 Weinheim 592 pp. Englisch.

Taschenbuch. Condición: Neu. Neuware - Fourth edition of a classic on computational physics with new chapters on data science, machine learning and general relativity, plus a plethora of supplementary materials.

Paperback. Condición: New. 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 relativity Computational 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 videos Computational Physics is ideal for students in physics, engineering, materials science, and any subjects drawing on applied physics.