Jan Glockauer; Wolfram Küper; Ute Lampert; Elke Schmidt-Wessel; Frank Schmidt; Karin Beck-Sprotte; Claudia Eichler Feldhaus Verlag GmbH + Co (2021) Pehmeäkantinen kirja
Christian Dierks; Albrecht Wienke; Wolfram Eberbach; Jörg Schmidtke; Hans-Dieter Lippert Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2003) Pehmeäkantinen kirja
Martin Grambow; Martin Grambow; Wolfram Mauser; Peter Wilderer; Wolfgang Gunthert; Hans Huber; Martin Steger; Schmidtke Springer Fachmedien Wiesbaden (2012) Pehmeäkantinen kirja
Jan Glockauer; Wolfram Küper; Ute Lampert; Martin Rugart; Frank Schmidt; Stephanie Weiß-Akgünyener; Elke H Schmidt Feldhaus Verlag GmbH + Co (2014) Pehmeäkantinen kirja
Jan Glockauer; Wolfram Küper; Ute Lampert; Martin Rugart; Frank Schmidt; Stephanie Weiß-Akgünyener; Elke-H. Schmidt Feldhaus Verlag GmbH + Co (2017) Pehmeäkantinen kirja
Jan Glockauer; Wolfram Küper; Ute Lampert; Martin Rugart; Frank Schmidt; Stephanie Weiß-Akgünyener; Elke-H. Schmidt Feldhaus Verlag GmbH + Co (2019) Pehmeäkantinen kirja
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.