Trending repositories for topic quantum-chemistry
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
The electronic structure package for quantum computers.
Open-Source Quantum Chemistry – an electronic structure package in C++ driven by Python
nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset
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.
Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics
Curated list of open-source quantum software projects.
Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics
nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset
Open-Source Quantum Chemistry – an electronic structure package in C++ driven by Python
The electronic structure package for quantum computers.
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
A curated list of Python packages related to 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.
Curated list of open-source quantum software projects.
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.
Open-Source Quantum Chemistry – an electronic structure package in C++ driven by Python
The electronic structure package for quantum computers.
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.
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
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.
Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics
Directory of Fortran codes on GitHub, arranged by topic
Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics
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.
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
Open-Source Quantum Chemistry – an electronic structure package in C++ driven by Python
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
A curated list of Python packages related to chemistry
The electronic structure package for quantum computers.
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Curated list of open-source quantum software projects.
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.
Open-Source Quantum Chemistry – an electronic structure package in C++ driven by Python
Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
The electronic structure package for quantum computers.
A curated list of Python packages related to chemistry
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
SchNetPack - Deep Neural Networks for Atomistic Systems
Structural Bioinformatics is awesome. Throw your textbook in the garbage, light the garbage can on fire, and blend the ashes into your cold brew almond milk latte and read this.
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
Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics
Structural Bioinformatics is awesome. Throw your textbook in the garbage, light the garbage can on fire, and blend the ashes into your cold brew almond milk latte and read this.
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
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.
A python package for exploring end-to-end chemistry workflows on quantum computers and simulators.
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
Automated Quantum Mechanical Environments (AQME) offers transparent and reproducible workflows available for Jupyter Notebooks and command lines, including: 1) RDKit- and CREST-based conformer generat...
Open-Source Quantum Chemistry – an electronic structure package in C++ driven by Python
The PennyLane-Cirq plugin integrates Google's Cirq software library with with PennyLane's quantum machine learning capabilities.
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.
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
Curated list of open-source quantum software projects.
A curated list of Python packages related to chemistry
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.
The electronic structure package for quantum computers.
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 ⚛️🧬💎.
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.
Directory of Fortran codes on GitHub, arranged by topic
nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset
A python package for exploring end-to-end chemistry workflows on quantum computers and simulators.
Orbital transfer and automatic multi-reference calculation for quantum chemistry
The SHARC molecular dynamics (MD) program suite is an ab initio MD software package developed to study the excited-state dynamics of molecules.
Ab initio full cell dynamical mean-field theory (DMFT) and GW+DMFT for solids
Efficient parallel quantum chemistry DMRG in MPO formalism
Python tools for automating routine tasks encountered when running quantum chemistry computations.