Star Cluster Evolution A Computational Guide

Written by a bestselling author, this is a modern view of the dynamics and evolution of star clusters combined with thorough coverage of the computational techniques. Targeted, relatively simple programs are used to demonstrate basic points of physics, whereby these programs may be linked to show how the combination of physical processes can lead to qualitatively new behavior. In addition, illustrative examples are provided for the novice. More advanced readers may experiment with the various modules (or write their own), allowing them to quickly modify the physics without having to make wholesale changes to the larger program. More technical issues, such as advanced algorithms, hardware acceleration, and high-performance parallel computing, are discussed in a series of appendices, with sample software compatible with the framework provided on a companion web site. This is a simplified and streamlined version of the authors' own MUSE research environment, and is compatible with the additional software found on the MUSE web site.
Aimed primarily at graduate students and post-docs, this is equally of interest to observers and researchers in related fields who might wish to model specific systems or processes of interest.

OVERVIEW
Observations of Star Clusters
- Open Clusters
- Globular Clusters
- Young Massive Clusters
- Galactiv Nuclei
Open Questions
STELLAR DYNAMICS
Models and Time Scales
- Dynamicsl Time
- Virial Equilibrium
- Commen Density Profiles
- Two-Body Relaxation
Particle Potential Solvers
- Direct Summation Codes
- Tree Codes
- Softening
Particle Integration Schemes
- Second- and Fourth-Order Methods
- Time Step Algorithms
External Fields
The Stellar Mass Function
Examples and Applications
- Violent Relaxation
- Mass Segregation
- Core Collapse
- Evaporation
STELLAR EVOLUTION
Modelling Stellar Evolution
- Toy Models
- Table Look-Up
- Self-Consistent Stellar Evolution Codes
Interfacing Stellar Evolution with Dynamics: The MUSE Modular Interface
Examples and Applications
- Mass Segregation with Stellar Evolution
- Core Collapse with Stellar Evolution
- Mass Loss and Cluster Lifetimes
BINARY DYNAMICS
Binary Properties
- Dynamically Formed Binaries
- "Primordial" Binaries
Numerical Methods
- Direct Integration
- Regularization
- Incorporation into the MUSE Framework
Examples and Applications
- Binary-Single Star Scattering;
Heggie's Law
- Binary-Binary Interactions
- Binary Ejection and Destruction
- Multiple Interactions
- Binary Heating in Star Clusters
BINARY EVOLUTION
Physical Processes
- Detached Evolution
- Semi-Detached Evolution
- Contact Evolution
- Mergers
Implementation in MUSE
- Simplified Models
- More Detailed Treatments
Examples and Applications
- Scattering Experiments: Punctated Binary Evolution
- Population Synthesis with and without Dynamics
STELLAR INTERACTIONS AND COLLISIONS
Collisions and Mergers
- Direct Interactions
- Binary-Mediated Interactions
- Mergers from Binary Evolution
- Observational Consequences
Modeling Stellar Mergers
- Sticky Spheres
- Entropy and Density Sorting
Examples and Applications
- Mergers and Mass Loss
- Blue Stragglers
- Low-Mass X-Ray Binaries
MODELING DENSE STELLAR SYSTEMS
Observations and Initial Conditions
Early Cluster Evolution
OB Dynamical Runaways
Collision Runaways
Black Hole Self-Ejection
APPENDIX A: INITIAL CONDITIONS
Stellar Mass Function
Mass Segregation
Virial Ratio
Spatial Density and Velocity Distributions
Tidal Field
Binary Fraction
Binary Secondary Masses
Binary Orbital Elements
Higher-Order Multiples
APPENDIX B: COMMON DIAGNOSTICS
Global Quantities
- Total Mass and Energy
- Virial Radius
- Center of Mass
- Density Center
Lagrangian Radii
Core Radius
Density and Luminosity Profiles
Stellar Mass and Luminosity Distributions
- Total
- By Percentile
Velocity Dispersion and Anisotropy
- Total
- By Percentile
Binary Properties
- Total
- By Percentile
APPENDIX C: MUSE IMPLEMENTATION DETAILS
The MUSE Software Framework
Modular Structure
Modules and Interfaces
Sample Scripts
APPENDIX D: HIGH-PERFORMANCE DYNAMICS
Parallel Implementations
The GRAPE Project
Acceleration Using Graphics Processing Units

Steve McMillan earned a BA in Mathematics from Cambridge University in 1977 and a Ph.D in Astronomy from Harvard in 1983. He joined the Physics Department at Drexel University in 1987 and is currently distinguished Professor of Physics at Drexel. His professional interests include numerical simulation of stars and stellar systems, development of high-performance software for star cluster simulations, and the analysis and visualization of complex datasets. He is also co-author of two best-selling introductory astronomy textbooks.

Simon Portegies Zwart got his Ph.D at Utrecht University in 1996. He worked as a postdoctoral fellow at the University of Amsterdam, Tokyo University (Japan), MIT (USA), and in Amsterdam. He is now Professor of Computational Astrophysics at the Sterrewacht Leiden. In 2007 he received the "Pastoor Schmeits" Prize for the most outstanding young Dutch astronomer, and in 2009 he received the VICI award for his research on star clusters.
His professional interests are high-performance computing and gravitational stellar dynamics, particularly in the context of the ecology of dense stellar systems.