ESPResSo is a versatile particle-based simulation package for molecular dynamics, fluid dynamics and Monte Carlo reaction schemes [1,2]. It provides numerical solvers for electrostatics, magnetostatics, hydrodynamics, electrokinetics, and diffusion-advection-reaction equations. It is designed as an MPI-parallel and GPU-accelerated simulation core written in C++ and CUDA, with a scripting interface in Python which integrates well with science and visualization packages in the Python ecosystem, such as NumPy and PyOpenGL. Its modularity and extensibility made it a popular tool in soft matter physics, where it has been used to simulate ionic liquids, polyelectrolytes, liquid crystals, colloids, ferrofluids and biological systems such as DNA and lipid membranes. Some research applications lead to the development of specialized codes that use ESPResSo as a library, such as molecular builders (pyMBE [3], pyOIF [4], pressomancy [5]), reinforcement learning frameworks (SwarmRL [6]) and systematic coarse-graining frameworks (VOTCA [7,8]). 

Many soft matter systems are characterized by physical properties that resolve different time- or length-scales. To fully capture these effects in a simulation, a multiscale approach is needed. Often, long-range interactions can be resolved very efficiently with minimal loss of accuracy using grid-based solvers, such as the particle–particle–particle mesh (P3M) algorithm for electrostatics and magnetostatics. Similarly, solute–solvent interactions can be approximated using the lattice-Boltzmann (LB) method for hydrodynamics, where the dense solvent is discretized on a grid and exchanges momentum with solid particles that represent the solute. These techniques not only bring the computational costs down, they also consume several orders of magnitude less computer memory compared to an atomistically-resolved system and require less bandwidth during communication between HPC nodes. 

Choice of simulation scenarios

We opted for three main simulation scenarii that are described in more detail in Deliverable 2.1 [9]. They have been written in a backward-compatible way, such that ESPResSo releases 4.2 and 5.0 can execute them, despite the API changes between both versions. 

The Lennard-Jones (LJ) scenario consists of soft spheres interacting with a short-range potential [10]. This simple setup underpins most particle-based simulations, where a weakly attractive, strongly repulsive pairwise potential is required to prevent particles from overlapping with one another. In addition, solvated systems with atomistic resolution typically have a large excess of solvent atoms compared to solute atoms; thus, LJ interactions tend to account for a large portion of the simulation time. The test simulates a Lennard-Jones fluid in the NVT ensemble and compares its pressure and total energy against expected values for the given volume, temperature, and particle number. 

The ionic crystal scenario (P3M) builds upon the LJ scenario and adds an electrical charge to the particles [11]. Since the Coulomb interaction decays with the inverse of the distance, it is necessary to include periodic image contributions to the particle forces. This is achieved using long-range numerical solvers, which leverage the fast Fourier transform (FFT) algorithm to calculate forces in an efficient manner. This type of simulation finds many applications in soft matter research, such as ionic liquid-based batteries, supercapacitors, and polyelectrolytes (gelling agents, charged biomolecules). The test models an ionic crystal, whose electrostatic potential can be directly compared against the Madelung constant. 

The hydrodynamics scenario is based on the LB method and models a dense, compressible fluid [12]. It was chosen due to the importance of hydrodynamic interactions in many physical systems at the mesoscale. While an atomistic description of solvent molecules is justifiable at the nanoscale, at the scale of micrometers a continuum-based description of the solvent is significantly less computationally demanding. It is also much more accurate than implicit solvent models, which do not adequately capture motion correlation in particles that are close to each other. With hydrodynamics and particle coupling, elements of fluid are resolved on a grid, allowing for momentum transfer between particles mediated via the fluid at the speed of sound. The test simulates a thermalized quiescent fluid with or without particles and verifies momentum conservation. 

Running the testsuite

ESPResSo can be either compiled from sources using the instructions in the user manual [13] or loaded from the EESSI repository. Loading the latest version of ESPResSo from dev.eessi.io involves the following steps, assuming the workstation is equipped with an AMD microprocessor: