The Active Matter Evaluation Package (AMEP) - a Python library for the analysis of particle-based and continuum simulation data of soft and active matter systems

Agent-based simulation of social interaction (Social Force Model and Self-Propelled Brownian Particles)

Brownian dynamics simulation is very insightful in the study of mechanical properties of complex fluids. In my MS project , I did such a simulation to study the properties of time dependent viscoelastic fluid, like special paints and Laponite suspensions. We modelled the system with an appropriate combination of springs and dampers.

An attempt to reproduce the findings presented in ‘’Simulation of a Brownian particle in an optical trap’’, Giorgio Volpe et al., Am. J. Phys. 81, 224–230 (2013))

Numerical approximations for stochastic differential equations.

Materials developed to Computational Physics course.

This repository contains the software written for the manuscript "When velocity autocorrelations mirror force autocorrelations: Exact noise-cancellation in interacting Brownian systems" by A. Lüders, S. Mandal, and T. Franosch. The NC Algorithm [Mandal et al. PRL 2019] is implemented using the FACF.

Open-source Brownian Dynamics Simulator OBDS. Developed this to test some ideas for developing a BDS.

Python package for simulation and data analysis of interacting colloidal particle systems.

Integration of the overdamped Langevin equations for an active Brownian circle swimmer (ABC).

This is the C++ code which generates the flocking simulations with fuel consumption. Starting with random positions and orientations, particles aggregate and flock when consuming the fuel. After running out fuel the system becomes passive and particles disperse.