souvik-snh / deep-learning-slow-modes

Supporting data for the manuscript "Deep learning the slow modes for rare events sampling"

Deep learning the slow modes for rare events sampling

Luigi Bonati, GiovanniMaria Piccini, and Michele Parrinello, arXiv preprint arXiv:2107.03943 (2021).

This repository contains input data and code related to the manuscript:

• data --> input files for the simulations and the CVs training
• mlcvs --> python package to train the Deep-TICA CVs
• plumed-libtorch-interface --> interface to load Pytorch models in PLUMED2 for enhanced sampling
• tutorial --> jupyter notebook with tutorial to train the CVs

Due to size limits the outputs trajectories of Chignolin and Silicon simulations are deposited in the Materials Cloud repository.