Trending repositories for topic quantum-chemistry
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
SchNetPack - Deep Neural Networks for Atomistic Systems
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
SchNetPack - Deep Neural Networks for Atomistic Systems
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
SchNetPack - Deep Neural Networks for Atomistic Systems
Open-Source Quantum Chemistry – an electronic structure package in C++ driven by Python
Curated list of open-source quantum software projects.
GradDFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation functionals using machine learning techniques.
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics
GradDFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation functionals using machine learning techniques.
Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
SchNetPack - Deep Neural Networks for Atomistic Systems
Open-Source Quantum Chemistry – an electronic structure package in C++ driven by Python
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
Curated list of open-source quantum software projects.
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
Curated list of open-source quantum software projects.
The electronic structure package for quantum computers.
Open-Source Quantum Chemistry – an electronic structure package in C++ driven by Python
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
A curated list of Python packages related to chemistry
Main repository for QMCPACK, an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance p...
SchNetPack - Deep Neural Networks for Atomistic Systems
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset
quacc is a flexible platform for computational materials science and quantum chemistry that is built for the big data era.
Directory of Fortran codes on GitHub, arranged by topic
GradDFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation functionals using machine learning techniques.
Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics
GradDFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation functionals using machine learning techniques.
nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset
quacc is a flexible platform for computational materials science and quantum chemistry that is built for the big data era.
Main repository for QMCPACK, an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance p...
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
Efficient parallel quantum chemistry DMRG in MPO formalism
Orbital transfer and automatic multi-reference calculation for quantum chemistry
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
Directory of Fortran codes on GitHub, arranged by topic
Curated list of open-source quantum software projects.
A python package for exploring end-to-end chemistry workflows on quantum computers and simulators.
Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
Curated list of open-source quantum software projects.
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
A curated list of Python packages related to chemistry
Open-Source Quantum Chemistry – an electronic structure package in C++ driven by Python
SchNetPack - Deep Neural Networks for Atomistic Systems
The electronic structure package for quantum computers.
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
Directory of Fortran codes on GitHub, arranged by topic
quacc is a flexible platform for computational materials science and quantum chemistry that is built for the big data era.
nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset
Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics
Interactive Jupyter Notebooks for learning the fundamentals of Density-Functional Theory (DFT)
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
Qrisp - a framework for high-level programming of Quantum computers
GradDFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation functionals using machine learning techniques.
quacc is a flexible platform for computational materials science and quantum chemistry that is built for the big data era.
nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset
Ab initio full cell dynamical mean-field theory (DMFT) and GW+DMFT for solids
Directory of Fortran codes on GitHub, arranged by topic
A python package for exploring end-to-end chemistry workflows on quantum computers and simulators.
The SHARC molecular dynamics (MD) program suite is an ab initio MD software package developed to study the excited-state dynamics of molecules.
Efficient parallel quantum chemistry DMRG in MPO formalism
Python suite for optimization of stationary points on ground- and excited states PES and determination of reaction paths.