aimmd

aimmd#

aimmd (AI for Molecular Mechanism Discovery) autonomously steers (a large number of) molecular dynamics simulations to efficiently sample and understand rare transition events.

If you use aimmd in published work please cite:

  • H. Jung, R. Covino, A. Arjun, C. Leitold, C. Dellago, P.G. Bolhuis and G. Hummer. Machine-guided path sampling to discover mechanisms of molecular self-organization. Nature Computational Science 3, 334–345 (2023). doi:10.1038/s43588-023-00428-z

Get started#

This section contains everything to get you started using aimmd.

The Basics

You might also want to have a look at the example jupyter notebooks below.

User guide#

TODO: This section does not exist yet! When it will be written it will provide more in-depth explanations on various topics, including some theoretic background and references for further reading.

User guide

Community guide#

The following section contains information on how to get help and/or report any issues encountered using aimmd as well as how to contribute code or documentation.

Community

Example notebooks#

This section contains example jupyter notebooks (also included in the repository) on various topics.

Example notebooks

Module layout

Changelog and Indices

Contents