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
An optimizer for quantum chemical calculation including artificial force induced reaction method
Source code for Automatic Differentiation for the Direct Minimization Approach to the Hartree-Fock 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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