| ISBN13: | 9781032981895 |
| ISBN10: | 103298189X |
| Kötéstípus: | Keménykötés |
| Terjedelem: | 214 oldal |
| Méret: | 234x156 mm |
| Nyelv: | angol |
| Illusztrációk: | 1 Illustrations, black & white; 111 Illustrations, color; 8 Halftones, color; 1 Line drawings, black & white; 103 Line drawings, color |
| 700 |
Python Experiments in Physics and Astronomy
GBP 79.99
Kattintson ide a feliratkozáshoz
Python Experiments in Physics and Astronomy acts as a resource for science and engineering students or faculty who would like to see how a diverse selection of topics can be analyzed and simulated using Python programs.
Python Experiments in Physics and Astronomy acts as a resource for science and engineering students or faculty who would like to see how a diverse selection of topics can be analyzed and simulated using Python programs. The book also provides Python solutions that can be learned from and modified as needed. The book is mainly aimed at undergraduates, but since many science students and faculty have limited exposure to scientific programming, having a collection of examples that address curve-fitting, Fast Fourier Transforms, image photometry and image alignment, and many others could be very helpful not just for learning from, but also to support classroom projects and demonstrations.
Key Features:
- Features tutorials using Python for non-computer science students and faculty involved with scientific programming
- Contains complete scientific programming examples for teaching and academic projects
- Presents detailed Python solutions for Physics and Astronomy topics, not normally covered in depth, because they would be too time-consuming
At last, an invaluable collection of software templates for practical problems in physics and astronomy written for students in the Python universe. Applications to aerodynamics, rocketry, and data fitting create a brilliant and rarely found merging across the boundaries of science and engineering. With tutorials, examples, and solutions, faculty will find this book to be an indispensable classroom resource for students at all levels.
- Richard Binzel, Professor of Planetary Science, Massachusetts Institute of Technology (MIT), March 2025
1. Python and Object Oriented Design Notes. 2. Exploring Data. 3. Signals and Trends. 4. Gravity Fields and Mass Distributions. 5. Spiral Galaxies and Dark Matter. 6. Sampling a Distribution. 7. Projectiles ? The German 88. 8. Rocket Launches. 9. Building a star catalog from an image. 10. Photometry: Measuring object brightness. 11. Aligning Images and Finding Targets. 12. The Saha Equation and the Balmer Spectrum. 13. Isochrons ? The Ages of Rocks.
