N-body simulations and trajectory analysis rely on the calculation of attributes that depend on pairwise particle distances within a cutoff. Interparticle potential energies, forces, distribution functions, neighbor lists, and distance-dependent distributions, for example, must be calculated. Cell lists are widely used to avoid computing distances outside the cutoff. However, efficient cell list implementations are difficult to customize. Here, we provide a fast and parallel implementation of cell lists in Julia that allows the mapping of custom functions dependent on particle positions in 2 or 3 dimensions. Arbitrary periodic boundary conditions are supported. Automatic differentiation and unit propagation can be used. The implementation provides a framework for the development of new analysis tools and simulations with custom potentials. The performance of resulting computations is comparable to state-of-the-art implementations of neighbor list algorithms and cell lists, available in specialized software. Examples are provided for the computation of potential energies, forces, distribution of pairwise velocities, neighbor lists and other typical calculations in molecular and astrophysical simulations. The Julia package is freely available at http://m3g.github.io/CellListMap.jl. Interfacing with Python and R with minimal overhead is possible.
Reference:
L. Martínez, CellListMap.jl: Efficient and customizable cell list implementation for calculation of pairwise particle properties within a cutoff. Computer Physics Communications, 279, 108452, 2022. https://doi.org/10.1016/j.cpc.2022.108452