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Numerical Python in astronomy and as...
~
Schmidt, Wolfram.
Numerical Python in astronomy and astrophysicsa practical guide to astrophysical problem solving /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Numerical Python in astronomy and astrophysicsby Wolfram Schmidt, Marcel Volschow.
Reminder of title:
a practical guide to astrophysical problem solving /
Author:
Schmidt, Wolfram.
other author:
Volschow, Marcel.
Published:
Cham :Springer International Publishing :2021.
Description:
x, 250 p. :ill., digital ;24 cm.
Contained By:
Springer Nature eBook
Subject:
AstronomyData processing.
Online resource:
https://doi.org/10.1007/978-3-030-70347-9
ISBN:
9783030703479$q(electronic bk.)
Numerical Python in astronomy and astrophysicsa practical guide to astrophysical problem solving /
Schmidt, Wolfram.
Numerical Python in astronomy and astrophysics
a practical guide to astrophysical problem solving /[electronic resource] :by Wolfram Schmidt, Marcel Volschow. - Cham :Springer International Publishing :2021. - x, 250 p. :ill., digital ;24 cm. - Undergraduate lecture notes in physics,2192-4791. - Undergraduate lecture notes in physics..
Chapter 1. Introduction -- Chapter 2. Getting Started with Python -- Chapter 3. Computing and Displaying Data -- Chapter 4. Functions and Numerical Methods -- Chapter 5. Solving Differential Equations -- Chapter 6. Astronomical Data Analysis.
This book provides a solid foundation in the Python programming language, numerical methods, and data analysis, all embedded within the context of astronomy and astrophysics. It not only enables students to learn programming with the aid of examples from these fields but also provides ample motivation for engagement in independent research. The book opens by outlining the importance of computational methods and programming algorithms in contemporary astronomical and astrophysical research, showing why programming in Python is a good choice for beginners. The performance of basic calculations with Python is then explained with reference to, for example, Kepler's laws of planetary motion and gravitational and tidal forces. Here, essential background knowledge is provided as necessary. Subsequent chapters are designed to teach the reader to define and use important functions in Python and to utilize numerical methods to solve differential equations and landmark dynamical problems in astrophysics. Finally, the analysis of astronomical data is discussed, with various hands-on examples as well as guidance on astronomical image analysis and applications of artificial neural networks.
ISBN: 9783030703479$q(electronic bk.)
Standard No.: 10.1007/978-3-030-70347-9doiSubjects--Topical Terms:
345333
Astronomy
--Data processing.
LC Class. No.: QB51.3.E43 / S36 2021
Dewey Class. No.: 522
Numerical Python in astronomy and astrophysicsa practical guide to astrophysical problem solving /
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Chapter 1. Introduction -- Chapter 2. Getting Started with Python -- Chapter 3. Computing and Displaying Data -- Chapter 4. Functions and Numerical Methods -- Chapter 5. Solving Differential Equations -- Chapter 6. Astronomical Data Analysis.
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This book provides a solid foundation in the Python programming language, numerical methods, and data analysis, all embedded within the context of astronomy and astrophysics. It not only enables students to learn programming with the aid of examples from these fields but also provides ample motivation for engagement in independent research. The book opens by outlining the importance of computational methods and programming algorithms in contemporary astronomical and astrophysical research, showing why programming in Python is a good choice for beginners. The performance of basic calculations with Python is then explained with reference to, for example, Kepler's laws of planetary motion and gravitational and tidal forces. Here, essential background knowledge is provided as necessary. Subsequent chapters are designed to teach the reader to define and use important functions in Python and to utilize numerical methods to solve differential equations and landmark dynamical problems in astrophysics. Finally, the analysis of astronomical data is discussed, with various hands-on examples as well as guidance on astronomical image analysis and applications of artificial neural networks.
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EB QB51.3.E43 S349 2021 2021
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https://doi.org/10.1007/978-3-030-70347-9
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