Numerical Python in Astronomy and Astrophysics - A Practical Guide to Astrophysical Problem Solving (Paperback, 1st ed. 2021)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Undergraduate Lecture Notes in Physics
Release date:	July 2021
First published:	2021
Authors:	Wolfram Schmidt • Marcel Voelschow
Dimensions:	235 x 155 x 18mm (L x W x T)
Format:	Paperback
Pages:	250
Edition:	1st ed. 2021
ISBN-13:	978-3-03-070346-2
Categories:	Books > Science & Mathematics > Astronomy, space & time > General Books > Science & Mathematics > Physics > General Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Science & Mathematics > Mathematics > Applied mathematics > General Books > Computing & IT > Computer programming > Programming languages > General Promotions
LSN:	3-03-070346-0
Barcode:	9783030703462

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