HOOMD-blue is a general-purpose particle simulation toolkit. It scales from a single CPU core to thousands of GPUs.
You define particle initial conditions and interactions in a high-level python script. Then tell HOOMD-blue how you want to execute the job and it takes care of the rest. Python job scripts give you unlimited flexibility to create custom initialization routines, control simulation parameters, and perform in situ analysis.

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The freud library provides users the ability to analyze molecular dynamics and Monte Carlo simulation trajectories for advanced metrics such as the radial distribution function and various order parameters. Its modules work with and return NumPy arrays, and are able to process both 2D and 3D data. Features in freud include computing the radial distribution function, local density, hexagonal order parameter and local bond order parameters, Voronoi tessellations, k-space quantities, and more. Documentation and examples are available via the freud repository.


The signac framework aids in the management of large and heterogeneous data spaces. It provides a simple and robust data model to create a well-defined indexable storage layout for data and metadata. This makes it easier to operate on large data spaces, streamlines post-processing and analysis and makes data collectively accessible.
Signac is open-source and freely available for Python versions 3.6+. For more details about signac and how to get started please visit the signac website.


plato is a python library for visualization of many-particle systems. It is able to render collections of objects using a range of interactive (for live analysis) or static (for use in scripted workflows) rendering backends. Documentation and examples are available for browsing.


pythia is a wrapper library around freud that is focused on generating descriptors of particle systems for machine learning applications. Documentation and examples are available for browsing.

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