Generally Applicable Atomic-Charge Dependent London Dispersion Correction
GradDFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation functionals using machine learning techniques.
Efficient parallel quantum chemistry DMRG in MPO formalism
Quantum computational chemistry based on TensorCircuit
Library first implementation of the D3 dispersion correction
Implementation of a machine learned density functional
A python wrapper for https://www.chemie.uni-bonn.de/pctc/mulliken-center/software/dft-d3/get-the-current-version-of-dft-d3
State Interaction Spin-Orbit (SISO) Method for CASSCF and FCI
Demos for the 2022 Many Electron Collaboration Workshop on PySCF
Source code for Automatic Differentiation for the Direct Minimization Approach to the Hartree-Fock Method
An optimizer for quantum chemical calculation including artificial force induced reaction method
A trial to implement doubly-hybrid interface to PySCF
Automatic diagram and code generation of quantum chemistry coupled-cluster equations
Implementation of local algorithms within pyscf
Green's function methods using auxiliary space
Quantum computational chemistry based on TensorCircuit
Fast-randomized iteration for coupled cluster.
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