Arif-PhyChem

MLQD

MLQD is a Python Package for Machine Learning-based Quantum Dissipative Dynamics

QD3SET

The first and the only dataset in the field of Quantum Dissipative Dynamics

Quantum_dissipative_dynamics_with_kernel_methods

Speeding up quantum dissipative dynamics of open systems with kernel methods

AIQD_FMO

Script for data generation and Code for our article "Predicting the future of excitation energy transfer in light-harvesting complex with artificial intelligence-based quantum dynamics"

OSTL

Code and data for our paper in JPCL "One-Shot Trajectory Learning of Open Quantum Systems Dynamics" https://doi.org/10.1021/acs.jpclett.2c01242

heom-lab

A Matlab implementation of the Hierarchical Equations of Motion (HEOM) method for modelling open system quantum dynamics.

CECAM_2022_colab_PS4

LearningExcitonTransfer

markdown-cheatsheet

Markdown Cheatsheet for Github Readme.md

MLinQCbook16-NAMD

Supplementary material for the chapter "Excited-state dynamics with machine learning" in the book "Quantum Chemistry in the Age of Machine Learning".

Quantum-Dynamics-in-MATLAB

In this repository, we release the numerical methods used for the paper https://iopscience.iop.org/article/10.1088/1361-6404/ab8360. The algorithms are used to solve both closed and open dynamics in quantum systems, where the codes are presented in the MATLAB language.

quantum_HEOM

A tool to model the bath relaxation dynamics of open quantum systems by Lindblad and Hierarchical Equations of Motion (HEOM) approaches.

qutip-notebooks

A collection of IPython notebooks using QuTiP: examples, tutorials, development test, etc.