AMUSE-Tutorial

Here are a number of small AMUSE tutorials in the form of python notebooks. These tutorials will (in part) be used for the AMUSE summer school 2022 at Geneva Observatory, June 2022.

Responsibility --so-far-- is by Simon Portegies Zwart But anybody who would like to contribute is welcome.

List of tutorials:

scalar_units.ipynb

Exploring some of the capabilities of units in AMUSE

Learning objectives

• How to import AMUSE modules.
• Declare variable and parameters with units.
• Perform simple mathematical operations on variables with units.
• Printing results in your preferred units.

particles.ipynb

Handling particles

excell_to_particleset.ipynb

Converting external data formats to a common AMUSE particle set

Learning objectives

• Initialize particle sets.
• Assign values to particle-set attributes.
• Use particle-set member functions.
• Assign a new attribute to a particle set.
• Manipulate particle sets.
• Query particle sets and get help.
• Select specific particles from a set.

Not discussed in this tutorial, but probably desired are:

• Initialize vector attributes in a particle set
• check for the existence of an attribute
• particle Supersets and Subsets
• synchronize_to()
• get_subset_from()

Nemesis_and_the_Sun.ipynb

Learn how to use modules and set up binary and multiple systems.

Learning objectives

• Set-up a particle set.
• Initialize planetary system.
• Converting orbital elements to Cartesian coordinates.
• Generate binary from orbital elements.

running_an_Nbody_code.ipynb

perform simple N-boyd simulation

Learning objectives

• How to generate inital conditions using built-in functions:
  • How to generate a mass-function.
  • How to generate a point-symmetric density distribution of particles.
• Initializing a direct gravitational N-body code.
• Initialize and use channels for intra-code data transfer.
• Detecting binaries.
• Simple plotting using matplotlib and AMUSE-native overloads.
• Making cumulative distributions

running_stellarevolution.ipynb

Perform simple stellar evolution calculation by setting up a stellar mass-function, declaring the stellar evolution code and run it to a certain moment in time.

Learning objectives

• Generate stellar mass-function from internal AMUSE routine.
• Plot the results.
• Use channels from and to running modules.

running_Nbdoy_with_stellar.ipynb

Run a stellar evolution code as well as an N-body code and assure that the result is self consistent.

Learning objectives

• Initiate multiple independent codes.
• exchange information from one code to another.
• Use Channels across modules.
• Plot results.

running_Nbody_with_collisions.ipynb

Perform an N-body calculation that includes stellar evolution and collisions between stars.

Learning objectives

• Channels
• Generate initial conditions.
• Initialize stellar and N-body codes.
• More advanced channels for copying specific attributes.
• Sstopping conditions.
• Initiate collision detection.
• Find a specific particle in another particle set.
• Merge stars.
• How to find an interacting subset of particles

bridged_Nbody_with_Galaxy.ipynb

Simulate a single star (and a cluster) in orbit around the Galactic center.

Learning objectives

• Single-directional hierarchical code coupling strategy (i.e. classice bridge).
• Bridge timesteps.
• Constructing classes in Python
• Incorporating an external potential to an N-body simulation
• Appreciate the role of get_gravity_at_point function in bridge.
• Appreciate the role of get_potential_at_point function in bridge.

gravity_cascaded_bridges.ipynb

Simulate several planetary system, each with their own N-body integrator, and the lot integrated in another N-body code. Note that here the interactions of one planet to the planets around another star are ignored in this implementation.

Learning objectives

• use a cascade of bridges

high_order_bridge.ipynb

Not yet documented Not yet working You simulate a debris disk around a moon, in orbit around a planet, in orbit around a star. This requires a higher order bridge, in order to assure that the orbital integration is performed with sufficient precision and accuracy.

Learning objectives

• Initialize a two-way bridge
• High-order bridge initalization
• How to construct a disk around a celestial body.

hierachical_bridges.ipynb

Not yet documented Construct a hierarchial bridge to integrate a highly hierarchical system of star and planets.

Learning objectives

• Non-linear coupling strategies (bridge).
• Hierarchical coupling strategies (bridge).
• Multiple channels to single particle set.

running_hydrodynamics.ipynb

Evolve a massive single star up to the moment it explodes in a supernova. After this we inject energy into the inner-region of the star and follow the hydrodynamics of the explosion by means of a smoothed-particle hydrodynamics code.

Learning objectives

• Run another AMUSE module to generate initial conditions for yet another code.
• How to recove the crash of a code and pick-up the result.
• Store simulation data in the form if python pickel files, and recover from those.
• plot the result of a hydrodynamical simulation.
• make an animation of simulation results.
• Run an AMUSE module as a parallel job.

bridge_gravity_with_hydro.ipynb

evolve_stars_asynchroneously.ipynb

• learn how to construct a population of stars that did not co-evolve

running_radiative_transport.ipynb

Not yet constructed

License

MIT