• 1. Introduction
  • 1.1. Guiding principles
  • 1.2. Basic program structure
  • 1.3. Basic python simulation script
  • 1.4. Tutorials
  • 1.5. Sample scripts
  • 1.6. On units
  • 1.7. Available simulation methods
  • 1.8. Software releases
    • 1.8.1. Release workflow
    • 1.8.2. Intended interface compatibility between ESPResSo versions
    • 1.8.3. How to cite ESPResSo
• 2. Installation
  • 2.1. Requirements
    • 2.1.1. Installing requirements on Ubuntu Linux
    • 2.1.2. Installing requirements on other Linux distributions
    • 2.1.3. Installing requirements on Mac OS X
  • 2.2. Quick installation
  • 2.3. Features
    • 2.3.1. General features
    • 2.3.2. Fluid dynamics and fluid structure interaction
    • 2.3.3. Interaction features
    • 2.3.4. Debug messages
    • 2.3.5. Features marked as experimental
    • 2.3.6. External features
  • 2.4. Configuring
    • 2.4.1. myconfig.hpp: Activating and deactivating features
    • 2.4.2. cmake
    • 2.4.3. ccmake
    • 2.4.4. Options and Variables
  • 2.5. Compiling, testing and installing
  • 2.6. Running ESPResSo
    • 2.6.1. Executing a simulation script
    • 2.6.2. Running an interactive notebook
  • 2.7. Debugging ESPResSo
• 3. Setting up the system
  • 3.1. Setting global variables in Python
    • 3.1.1. Accessing module states
  • 3.2. Cellsystems
    • 3.2.1. Global properties
    • 3.2.2. Domain decomposition
    • 3.2.3. N-squared
    • 3.2.4. Layered cell system
  • 3.3. Thermostats
    • 3.3.1. Langevin thermostat
    • 3.3.2. Lattice-Boltzmann thermostat
    • 3.3.3. Dissipative Particle Dynamics (DPD)
    • 3.3.4. Isotropic NPT thermostat
  • 3.4. CUDA
    • 3.4.1. GPU Acceleration with CUDA
    • 3.4.2. List available CUDA devices
    • 3.4.3. Selection of CUDA device
• 4. Setting up particles
  • 4.1. Overview of the relevant Python classes
  • 4.2. Adding particles
  • 4.3. Accessing particle properties
    • 4.3.1. Vectorial properties
  • 4.4. Interacting with groups of particles
  • 4.5. Deleting particles
  • 4.6. Iterating over particles and pairs of particles
  • 4.7. Exclusions
  • 4.8. Create particular particle configurations
    • 4.8.1. Setting up polymer chains
    • 4.8.2. Setting up diamond polymer networks
  • 4.9. Virtual sites
    • 4.9.1. Rigid arrangements of particles
    • 4.9.2. Inertialess lattice-Boltzmann tracers
  • 4.10. Particle number counting feature
  • 4.11. Self-propelled swimmers
    • 4.11.1. Langevin swimmers
    • 4.11.2. Lattice-Boltzmann (LB) swimmers
• 5. Running the simulation
  • 5.1. Velocity Verlet algorithm
  • 5.2. Isotropic NPT integrator
  • 5.3. Rotational degrees of freedom and particle anisotropy
  • 5.4. Steepest descent
• 6. Non-bonded interactions
  • 6.1. Isotropic non-bonded interactions
    • 6.1.1. Tabulated interaction
    • 6.1.2. Lennard-Jones interaction
    • 6.1.3. Generic Lennard-Jones interaction
    • 6.1.4. Weeks–Chandler–Andersen interaction
    • 6.1.5. Lennard-Jones cosine interaction
    • 6.1.6. Smooth step interaction
    • 6.1.7. BMHTF potential
    • 6.1.8. Morse interaction
    • 6.1.9. Buckingham interaction
    • 6.1.10. Soft-sphere interaction
    • 6.1.11. Membrane-collision interaction
    • 6.1.12. Hat interaction
    • 6.1.13. Hertzian interaction
    • 6.1.14. Gaussian interaction
    • 6.1.15. DPD interaction
    • 6.1.16. Thole correction
  • 6.2. Anisotropic non-bonded interactions
    • 6.2.1. Gay–Berne interaction
• 7. Bonded interactions
  • 7.1. Distance-dependent bonds
    • 7.1.1. FENE bond
    • 7.1.2. Harmonic bond
    • 7.1.3. Harmonic Dumbbell Bond
    • 7.1.4. Quartic bond
    • 7.1.5. Bonded Coulomb
    • 7.1.6. Subtract P3M short-range bond
    • 7.1.7. Subtracted Lennard-Jones bond
    • 7.1.8. Rigid bonds
    • 7.1.9. Thermalized distance bond
    • 7.1.10. Tabulated distance
    • 7.1.11. Virtual bonds
  • 7.2. Bond-angle interactions
    • 7.2.1. Harmonic angle potential
    • 7.2.2. Cosine angle potential
    • 7.2.3. Harmonic cosine potential
    • 7.2.4. Tabulated angle potential
  • 7.3. Dihedral interactions
    • 7.3.1. Dihedral potential with phase shift
    • 7.3.2. Tabulated dihedral potential
  • 7.4. Object-in-fluid interactions
    • 7.4.1. OIF local forces
    • 7.4.2. OIF global forces
    • 7.4.3. Out direction
• 8. Electrostatics
  • 8.1. Coulomb P3M
    • 8.1.1. Tuning Coulomb P3M
    • 8.1.2. Coulomb P3M on GPU
  • 8.2. Debye-Hückel potential
  • 8.3. Dielectric interfaces with the ICC\(\star\) algorithm
  • 8.4. MMM2D
  • 8.5. Electrostatic Layer Correction (ELC)
  • 8.6. MMM1D
    • 8.6.1. MMM1D on GPU
  • 8.7. ScaFaCoS electrostatics
• 9. Magnetostatics / Dipolar interactions
  • 9.1. Dipolar interaction
    • 9.1.1. Dipolar P3M
    • 9.1.2. Dipolar Layer Correction (DLC)
  • 9.2. Dipolar direct sum
  • 9.3. Barnes-Hut octree sum on GPU
  • 9.4. ScaFaCoS magnetostatics
• 10. System manipulation
  • 10.1. Changing the box volume
  • 10.2. Stopping particles
  • 10.3. Fixing the center of mass
  • 10.4. Capping the force during warmup
  • 10.5. Galilei Transform and Particle Velocity Manipulation
• 11. Single particle forces (constraints)
  • 11.1. Shaped-based constraints
    • 11.1.1. Adding shape-based constraints to the system
    • 11.1.2. Deleting a constraint
    • 11.1.3. Getting the currently defined constraints
    • 11.1.4. Getting the force on a constraint
    • 11.1.5. Getting the minimal distance to a constraint
    • 11.1.6. Available shapes
    • 11.1.7. Available options
  • 11.2. External Fields
    • 11.2.1. Constant fields
    • 11.2.2. Interpolated Force and Potential fields
• 12. Lattice-Boltzmann
  • 12.1. Setting up a LB fluid
  • 12.2. Checkpointing LB
  • 12.3. Interpolating velocities
  • 12.4. Coupling LB to a MD simulation
  • 12.5. Reading and setting properties of single lattice nodes
  • 12.6. Removing total fluid momentum
  • 12.7. Output for visualization
  • 12.8. Choosing between the GPU and CPU implementations
  • 12.9. Electrohydrodynamics
  • 12.10. Using shapes as lattice-Boltzmann boundary
    • 12.10.1. Minimal usage example
    • 12.10.2. Setting up boundary conditions
• 13. Analysis
  • 13.1. Direct analysis routines
    • 13.1.1. Energies
    • 13.1.2. Momentum of the System
    • 13.1.3. Minimal distances between particles
    • 13.1.4. Particles in the neighborhood
    • 13.1.5. Particle distribution
    • 13.1.6. Cylindrical Average
    • 13.1.7. Radial distribution function
    • 13.1.8. Structure factor
    • 13.1.9. Center of mass
    • 13.1.10. Moment of inertia matrix
    • 13.1.11. Gyration tensor
    • 13.1.12. Pressure
    • 13.1.13. Stress Tensor
    • 13.1.14. Chains
  • 13.2. Observables and correlators
    • 13.2.1. Creating an observable
    • 13.2.2. Available observables
    • 13.2.3. Correlations
    • 13.2.4. Details of the multiple tau correlation algorithm
  • 13.3. Accumulators
    • 13.3.1. Time series
    • 13.3.2. Mean-variance calculator
  • 13.4. Cluster analysis
• 14. Input and Output
  • 14.1. Checkpointing and restoring a simulation
  • 14.2. Writing H5MD-files
  • 14.3. Writing MPI-IO binary files
  • 14.4. Writing VTF files
    • 14.4.1. writevsf: Writing the topology
    • 14.4.2. writevcf: Writing the coordinates
    • 14.4.3. espressomd.io.writer.vtf.vtf_pid_map()
  • 14.5. Writing various formats using MDAnalysis
  • 14.6. Reading various formats using MDAnalysis
  • 14.7. Parsing PDB Files
• 15. Online-visualization
  • 15.1. General usage
  • 15.2. Common methods for OpenGL and Mayavi
  • 15.3. Mayavi visualizer
  • 15.4. OpenGL visualizer
    • 15.4.1. Running the visualizer
    • 15.4.2. Screenshots
    • 15.4.3. Colors and Materials
    • 15.4.4. Visualize vectorial properties
    • 15.4.5. Controls
    • 15.4.6. Dragging particles
  • 15.5. Visualization example scripts
• 16. Advanced Methods
  • 16.1. Creating bonds when particles collide
  • 16.2. Immersed Boundary Method for soft elastic objects
  • 16.3. Object-in-fluid
    • 16.3.1. Triangulations of elastic objects
    • 16.3.2. Description of sample script
    • 16.3.3. Visualization in ParaView
    • 16.3.4. Available Object-in-fluid (OIF) classes
  • 16.4. Electrokinetics
    • 16.4.1. Electrokinetic Equations
    • 16.4.2. Setup
    • 16.4.3. Output
  • 16.5. Particle polarizability with thermalized cold Drude oscillators
    • 16.5.1. Canceling intramolecular electrostatics
  • 16.6. Monte Carlo Methods
    • 16.6.1. Reaction Ensemble
    • 16.6.2. Wang-Landau Reaction Ensemble
    • 16.6.3. Grand canonical ensemble simulation
    • 16.6.4. Constant pH simulation
    • 16.6.5. Widom Insertion (for homogeneous systems)
• 17. Under the hood
  • 17.1. Internal particle organization
• 18. Contributing
  • 18.1. Community support
  • 18.2. Contributing your own code
    • 18.2.1. Required Development Tools
  • 18.3. Building the User’s guide
• 19. Appendix
  • 19.1. The MMM family of algorithms
    • 19.1.1. Introduction
    • 19.1.2. MMM2D theory
    • 19.1.3. MMM1D theory
    • 19.1.4. ELC theory
    • 19.1.5. Errors
• 20. Bibliography