/tools

CP2K containers facilitate the use of CP2K software for molecular dynamics and quantum chemistry simulations. The containers are designed for various host systems and support running on HPC environments, making it easier to perform complex molecular simulations.

QuantNBody is a Python package designed for quantum chemistry and physics, enabling users to manipulate many-body operators and wave functions. It facilitates the construction of various quantum models and operators, making it useful for theoretical research and educational purposes in quantum mechanics.

The dmrgscf repository provides an interface for using DMRG and DMRGSCF methods as solvers for CASSCF calculations in quantum chemistry. It allows users to perform advanced molecular simulations and analyze electronic structures of molecules.

dftio is a tool designed to assist machine learning communities by transcribing and manipulating DFT output into a format suitable for machine learning models. It supports various DFT software and provides functionalities for parsing different molecular properties from the output data.

LSQT-Jupyter is a tutorial that demonstrates linear scaling quantum transport methods using Jupyter notebooks. It serves as an educational resource for understanding quantum transport in molecular systems, although it is not intended for high-performance computing applications.

The 'qchem' repository is a framework for molecular modeling that combines machine learning and quantum chemistry to explore molecular properties and datasets. It provides tools for implementing models and datasets in a modular and extendable manner, facilitating research in molecular simulations and property predictions.

CuGBasis is a high-performance library designed for efficient computation of quantum chemistry density-based descriptors using CUDA and Python. It enables the calculation of molecular orbitals, electron density, and other quantum chemistry properties, making it a valuable tool for researchers in computational chemistry.

EquiHGNN is a framework for scalable rotationally equivariant hypergraph neural networks aimed at improving molecular modeling. It integrates symmetry-aware representations to enhance predictions of molecular properties using various datasets, including QM9 and PCQM4Mv2.

AutoChem is a virtual chemical reactor that generates products from a pool of compounds and a set of reactions. It automates quantum chemistry calculations and prepares input files for various quantum chemistry software, facilitating the analysis of chemical reactions and their free energies.

pyqchem is a Python repository that contains routines for performing electronic structure calculations on atoms and small molecules. It allows users to execute various quantum chemistry methods, such as MP2, by modifying the script parameters.

The dftd3 package serves as an interface for the DFT-D3 method, allowing users to compute molecular energies and gradients. It is a drop-in replacement for the pyscf.dftd3 module, facilitating quantum chemical calculations for molecular systems.

This repository implements a method for orbital-free density functional theory using continuous-time normalizing flows to optimize molecular densities. It allows for simulations of electronic densities for various molecules, contributing to the field of computational chemistry.

This repository contains data for QM9 molecules and reactions, along with Python scripts for processing and analyzing molecular data. It enables users to download molecular data, create databases of atomization energies, and process reaction information, making it a valuable resource for computational chemistry research.

The Tensor Contraction Engine (TCE) is a symbolic algebra code that derives equations for ab initio electron-correlated theories and generates corresponding Fortran code for use in quantum chemistry software like NWCHEM. It facilitates the execution of complex quantum chemical calculations in parallel.

The xtbiff program is designed to implement a general intermolecular force field using tight-binding quantum chemical calculations. It can be utilized in molecular simulations and is compatible with other computational chemistry tools.

The Electron-Phonon Averaged (EPA) Approximation tool is designed to compute electron-phonon coupling and transport properties in materials. It utilizes a computational workflow involving Quantum ESPRESSO and BoltzTraP to analyze the electronic properties of materials like silicon and half-Heusler compounds.

PyFock-GUI is an interactive web application that enables users to perform density functional theory (DFT) calculations on molecules. It supports various exchange-correlation functionals and basis sets, allowing for the prediction of molecular properties and visualization of molecular orbitals in real-time.

The 'mlgf' repository provides tools for machine learning many-body Green's function calculations, enabling the prediction of various chemical properties derived from electronic structure data. It utilizes advanced machine learning algorithms to fit self-energy functionals and offers features for analyzing molecular excitation spectra.

Kylin-V is a software package designed for time-dependent density matrix renormalization group (TD-DMRG) and vibrational heat-bath configuration interaction (VHCI) methods. It provides improved code for simulating molecular systems without requiring unstable external libraries.

mbGDML is a tool for creating, using, and analyzing machine learning potentials within the many-body expansion framework. It allows for accurate predictions of molecular properties and supports molecular dynamics simulations, making it a valuable resource in computational chemistry.