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Sinopsis
This second edition introduces Python programming to readers with little or no prior experience, specifically tailored for physicists and natural sciences students. The book begins with interactive Python exercises to foster familiarity with the language. It then progresses to more complex Python scripts (programs) that readers are encouraged to run on their own computers. Each program listing is thoroughly explained, and readers are encouraged to experiment by modifying code lines or blocks to observe and understand their effects. The text introduces Matplotlib graphics for creating figures representing data, function plots, and visualizations like field lines and equipotential surfaces. It also explores 3D graphics and animated function plots. A dedicated chapter covers the numerical solution of algebraic and transcendental equations.
The underlying mathematical principles are thoroughly discussed and the available Python tools for solving these equations are presented. A further chapter is dedicated to the numerical solution of ordinary differential equations (ODEs). This is of vital importance for the physicist, since differential equations are at the base of both classical physics (Newton’s equations) and quantum mechanics (Schroedinger’s equation). The shooting method for the numerical solution of ordinary differential equations with boundary conditions is also presented. Python programs for the solution of two quantum-mechanics problems are discussed as examples. Two chapters are dedicated to Tkinter graphics, which gives the user more freedom than Matplotlib, and to Tkinter animation. A special chapter is dedicated to computer animation involving differential equations, with a discussion of the effect of the accumulation of truncation errors, particularly relevant for such fields as molecular dynamics or celestial mechanics, which often require integrating Newton’s equations over a very long time starting from some initial conditions. Symplectic algorithms for tackling this problem are introduced. Programs displaying the animation of physical problems involving the solution of ordinary differential equations (for which in most cases there is no algebraic solution) in real time are presented and discussed. Finally, 3D animation is presented with Vpython.
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Acerca del autor
Giovanni Moruzzi is a retired associate professor from the Physics Department at the University of Pisa, where he continues to teach a course on basic Python algorithms, with a particular focus on computer animation of physical phenomena.
His research interests encompass atomic and molecular spectroscopy, particularly the analysis and assignment of dense molecular spectra involving large-amplitude internal motions. He has authored over 70 papers in peer-reviewed journals and has contributed as both co-editor and co-author of two scientific books and two books on physics exercises
De la contraportada
This second edition introduces Python programming to readers with little or no prior experience, specifically tailored for physicists and natural sciences students. The book begins with interactive Python exercises to foster familiarity with the language. It then progresses to more complex Python scripts (programs) that readers are encouraged to run on their own computers. Each program listing is thoroughly explained, and readers are encouraged to experiment by modifying code lines or blocks to observe and understand their effects. The text introduces Matplotlib graphics for creating figures representing data, function plots, and visualizations like field lines and equipotential surfaces. It also explores 3D graphics and animated function plots. A dedicated chapter covers the numerical solution of algebraic and transcendental equations.
The underlying mathematical principles are thoroughly discussed and the available Python tools for solving these equations are presented. A further chapter is dedicated to the numerical solution of ordinary differential equations (ODEs). This is of vital importance for the physicist, since differential equations are at the base of both classical physics (Newton’s equations) and quantum mechanics (Schroedinger’s equation). The shooting method for the numerical solution of ordinary differential equations with boundary conditions is also presented. Python programs for the solution of two quantum-mechanics problems are discussed as examples. Two chapters are dedicated to Tkinter graphics, which gives the user more freedom than Matplotlib, and to Tkinter animation. A special chapter is dedicated to computer animation involving differential equations, with a discussion of the effect of the accumulation of truncation errors, particularly relevant for such fields as molecular dynamics or celestial mechanics, which often require integrating Newton’s equations over a very long time starting from some initial conditions. Symplectic algorithms for tackling this problem are introduced. Programs displaying the animation of physical problems involving the solution of ordinary differential equations (for which in most cases there is no algebraic solution) in real time are presented and discussed. Finally, 3D animation is presented with Vpython.
"Sobre este título" puede pertenecer a otra edición de este libro.
- EditorialSpringer International Publishing AG
- Año de publicación2025
- ISBN 10 3031945921
- ISBN 13 9783031945922
- EncuadernaciónTapa dura
- IdiomaInglés
- Número de edición2
- Número de páginas330
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Essential Python for the Physicist
Publicado por
Springer, Berlin, Springer Nature Switzerland, Springer International Publishing, Springer, 2025
ISBN 10: 3031945921
ISBN 13: 9783031945922
Nuevo
Tapa dura
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This second edition introduces Python programming to readers with little or no prior experience, specifically tailored for physicists and natural sciences students. The book begins with interactive Python exercises to foster familiarity with the language. It then progresses to more complex Python scripts (programs) that readers are encouraged to run on their own computers. Each program listing is thoroughly explained, and readers are encouraged to experiment by modifying code lines or blocks to observe and understand their effects. The text introduces Matplotlib graphics for creating figures representing data, function plots, and visualizations like field lines and equipotential surfaces. It also explores 3D graphics and animated function plots. A dedicated chapter covers the numerical solution of algebraic and transcendental equations.The underlying mathematical principles are thoroughly discussed and the available Python tools for solving these equations are presented. A further chapter is dedicated to the numerical solution of ordinary differential equations (ODEs). This is of vital importance for the physicist, since differential equations are at the base of both classical physics (Newton s equations) and quantum mechanics (Schroedinger s equation). The shooting method for the numerical solution of ordinary differential equations with boundary conditions is also presented. Python programs for the solution of two quantum-mechanics problems are discussed as examples. Two chapters are dedicated to Tkinter graphics, which gives the user more freedom than Matplotlib, and to Tkinter animation. A special chapter is dedicated to computer animation involving differential equations, with a discussion of the effect of the accumulation of truncation errors, particularly relevant for such fields as molecular dynamics or celestial mechanics, which often require integrating Newton s equations over a very long time starting from some initial conditions. Symplectic algorithms for tackling this problem are introduced. Programs displaying the animation of physical problems involving the solution of ordinary differential equations (for which in most cases there is no algebraic solution) in real time are presented and discussed. Finally, 3D animation is presented with Vpython. 330 pp. Englisch. Nº de ref. del artículo: 9783031945922
Cantidad disponible: 2 disponibles
Imagen del vendedor
Essential Python for the Physicist
Publicado por
Springer, Berlin, Springer Nature Switzerland, Springer International Publishing, Springer, 2025
ISBN 10: 3031945921
ISBN 13: 9783031945922
Nuevo
Tapa dura
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This second edition introduces Python programming to readers with little or no prior experience, specifically tailored for physicists and natural sciences students. The book begins with interactive Python exercises to foster familiarity with the language. It then progresses to more complex Python scripts (programs) that readers are encouraged to run on their own computers. Each program listing is thoroughly explained, and readers are encouraged to experiment by modifying code lines or blocks to observe and understand their effects. The text introduces Matplotlib graphics for creating figures representing data, function plots, and visualizations like field lines and equipotential surfaces. It also explores 3D graphics and animated function plots. A dedicated chapter covers the numerical solution of algebraic and transcendental equations.The underlying mathematical principles are thoroughly discussed and the available Python tools for solving these equations are presented. A further chapter is dedicated to the numerical solution of ordinary differential equations (ODEs). This is of vital importance for the physicist, since differential equations are at the base of both classical physics (Newton s equations) and quantum mechanics (Schroedinger s equation). The shooting method for the numerical solution of ordinary differential equations with boundary conditions is also presented. Python programs for the solution of two quantum-mechanics problems are discussed as examples. Two chapters are dedicated to Tkinter graphics, which gives the user more freedom than Matplotlib, and to Tkinter animation. A special chapter is dedicated to computer animation involving differential equations, with a discussion of the effect of the accumulation of truncation errors, particularly relevant for such fields as molecular dynamics or celestial mechanics, which often require integrating Newton s equations over a very long time starting from some initial conditions. Symplectic algorithms for tackling this problem are introduced. Programs displaying the animation of physical problems involving the solution of ordinary differential equations (for which in most cases there is no algebraic solution) in real time are presented and discussed. Finally, 3D animation is presented with Vpython. Nº de ref. del artículo: 9783031945922
Cantidad disponible: 2 disponibles