Computational astrophysics connects observational data with theoretical models, driven by advances in both telescope technology and computing power. As simulations grow in scale and realism, software must evolve to keep pace. This book introduces AMUSE, a Python-based framework for modular, multi-physics simulations, allowing users to combine solvers and build complex models. The updated edition supports Python 3 and includes new examples in hydrodynamics and planetary systems. It also offers practical guidance for running AMUSE on supercomputers, using SLURM, enabling GPU support, and executing multi-node simulations. With downloadable scripts and reproducible figures, it serves as a comprehensive resource for both beginners and experienced researchers in the field.
Key features:
- Provides an introduction to the fundamentals of computational astrophysics
- Second edition is considerably expanded with three new chapters and two appendices
- Update throughout to be compatible with Python Version 3
- Includes downloadable source code and python notebooks
