essential python physicist di moruzzi giovanni (36 risultati)

Condizione: New. 1st ed. 2020 edition NO-PA16APR2015-KAP.

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hardcover. Condizione: Fine.

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Hardcover. Condizione: new. Hardcover. 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 (Newtons equations) and quantum mechanics (Schroedingers 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 Newtons 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Condizione: As New. Unread book in perfect condition.

Buch. Condizione: Neu. 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. 400 pp. Englisch.

Condizione: New.

Condizione: New. In.

Hardcover. Condizione: new. Hardcover. 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 (Newtons equations) and quantum mechanics (Schroedingers 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 Newtons 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Taschenbuch. Condizione: Neu. Essential Python for the Physicist | Giovanni Moruzzi | Taschenbuch | x | Englisch | 2021 | Springer | EAN 9783030450298 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces the reader with little or no previous computer-programming experience to the Python programming language of interest for a physicist or a natural-sciences student. The book starts with basic interactive Python in order to acquire an introductory familiarity with the language, than tackle Python scripts (programs) of increasing complexity, that the reader is invited to run on her/his computer. All program listings are discussed in detail, and the reader is invited to experiment on what happens if some code lines are modified. The reader is introduced to Matplotlib graphics for the generation of figures representing data and function plots and, for instance, field lines. Animated function plots are also considered. A chapter is dedicated to the numerical solution of algebraic and transcendental equations, the basic mathematical principles are discussed and the available Python tools for the solution are presented. A further chapter is dedicated to the numerical solution of ordinary differential equations. 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 at two boundaries 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. 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.

Hardcover. Condizione: Brand New. 2nd har/psc edition. 330 pages. 9.25x6.10x9.41 inches. In Stock.

Buch. Condizione: 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.

Hardcover. Condizione: new. Hardcover. 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 (Newtons equations) and quantum mechanics (Schroedingers 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 Newtons 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces the reader with little or no previous computer-programming experience to the Python programming language of interest for a physicist or a natural-sciences student. The book starts with basic interactive Python in order to acquire an introductory familiarity with the language, than tackle Python scripts (programs) of increasing complexity, that the reader is invited to run on her/his computer. All program listings are discussed in detail, and the reader is invited to experiment on what happens if some code lines are modified. The reader is introduced to Matplotlib graphics for the generation of figures representing data and function plots and, for instance, field lines. Animated function plots are also considered. A chapter is dedicated to the numerical solution of algebraic and transcendental equations, the basic mathematical principles are discussed and the available Python tools for the solution are presented. A further chapter is dedicated to the numerical solution of ordinary differential equations. 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 at two boundaries 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. 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.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condizione: new. Questo è un articolo print on demand.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces the reader with little or no previous computer-programming experience to the Python programming language of interest for a physicist or a natural-sciences student. The book starts with basic interactive Python in order to acquire an introductory familiarity with the language, than tackle Python scripts (programs) of increasing complexity, that the reader is invited to run on her/his computer. All program listings are discussed in detail, and the reader is invited to experiment on what happens if some code lines are modified. The reader is introduced to Matplotlib graphics for the generation of figures representing data and function plots and, for instance, field lines. Animated function plots are also considered. A chapter is dedicated to the numerical solution of algebraic and transcendental equations, the basic mathematical principles are discussed and the available Python tools for the solution are presented. A further chapter is dedicated to the numerical solution of ordinary differential equations. 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 at two boundaries 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. 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. 302 pp. Englisch.