HOOMD-blue tutorials and examples

Welcome to the HOOMD-blue example scripts. These jupyter notebooks demonstrate how to utilize the functionality of HOOMD-blue. You can view a static version of the notebooks at nbviewer. See Installing HOOMD and other python packages for details on how to run these notebooks interactively.

Getting started

• Installing HOOMD and other python packages
• Executing scripts on the command line
• For full details on all HOOMD commands, see the reference documentation

See Notebook Basics and Running Code for tutorials on using jupyter itself.

Tutorials

HOOMD is a python package that provides a toolkit of commands to configure particle simulations. These tutorials demonstrate many commonly used features in HOOMD with fully functional and documented scripts that perform simulations and examine the output.

• Molecular dynamics
  • Lennard-Jones
  • DPD polymers
  • Rigid Rods
  • Active matter
• Hard particle Monte Carlo
  • Hard disks
  • Hard squares
• DEM
  • Rounded squares

Initializing simulations

This section includes more detailed examples on execution context and system initialization.

• Simulation contexts
• User options
• Create lattice
• Populate snapshot
• Initialize from a file

Specifying particle interactions

This section includes short examples of a variety of HOOMD features that control how particles interact.

• Molecular Dynamics
  • Multiple pair potentials
  • Bonds, angles, and dihedrals
  • Walls and constant forces
  • Long range electrostatics
  • Distance constraints
• Hard particle Monte Carlo
  • Confining shapes in walls

Writing output

This section includes examples that demonstrate how to write output from HOOMD simulations.

• Save GSD trajectories
• Store particle shape information in GSD files
• Generate bibtex files
• Record run metadata
• Log quantities to a file
• MD log quantities
• HPMC log quantities
• Controlling output verbosity

Running simulations

This section includes examples showing how to control simulation execution.

• Advancing simulations
• Walltime limits
• Restartable simulations
• Molecular dynamics
  • Integration methods
  • Energy minimization
  • Tuning neighbor list parameters
• Hard particle Monte Carlo
  • Selecting move sizes
  • Constant pressure
  • Quick compression scheme
• MPI parallel simulations
  • comm.get_rank
  • partitions

Analyzing simulation output

These notebooks demonstrate simple analysis techniques on the output of HOOMD simulations.

• Accessing system configurations in python
• HPMC
  • Measuring pressure at constant volume
• Visualization
  • OVITO
  • VMD
• Quantitative analysis
  • Online analysis with Freud