dynasor 2.3

Dynamical structure factors and correlation functions from molecular dynamics trajectories

dynasor is a tool for calculating total and partial dynamic structure factors as well as related correlation functions from molecular dynamics (MD) simulations. By analyzing these functions one can access the dynamics of a system without resorting to perturbative approaches. Moreover by combining in particular the structure factor with the cross sections (or form factors) of, e.g., neutrons, X-rays or electrons, one can predict experimental spectra. The main input consists of a trajectory from a MD simulation, i.e., a file containing snapshots of the particle coordinates and optionally velocities, that correspond to consecutively and equally spaced points in (simulation) time.

dynasor provides both python and a command line interface. The following snippet illustrates how one can calculate dynamic structure factors using the former.

traj = Trajectory('dump.xyz', trajectory_format='extxyz')
q_points = generate_spherical_qpoints(traj.cell, q_max=20)
sample = compute_dynamic_structure_factors(traj, q_points=q_points, dt=5, window_size=100)
sample.write_to_npy('test.npy')

dynasor can be installed via pip or conda. Please consult the installation section of the user guide for details.

The full documentation can be found in the user guide. For questions and help please use the dynasor discussion forum on matsci.org. dynasor and its development are hosted on gitlab.

When using dynasor in your research please cite the following papers:

Dynasor – A tool for extracting dynamical structure factors and current correlation functions from molecular dynamics simulations

Erik Fransson, Mattias Slabanja, Paul Erhart, and Göran Wahnström

Advanced Theory and Simulations 4, 2000240 (2021); DOI:10.1002/adts.202000240

Dynasor 2: From simulation to experiment through correlation functions

Esmée Berger, Erik Fransson, Fredrik Eriksson, Eric Lindgren, Göran Wahnström, Thomas Holm Rod, and Paul Erhart

Computer Physics Communications 316, 109759 (2025); DOI: 10.1016/j.cpc.2025.109759