18 citations · 54 across the 14 of their papers we have counts for
16 papers
Intrinsic Wannier Functions for Hamiltonian downfolding
Shuoxue Li, Garnet Kin-Lic Chan
Downfolding ab initio material band structure into a low-energy subspace spanned by orbitals of specified atomic character, a procedure known as Wannier downfolding, is a common ta…
The Python Simulations of Chemistry Framework: 10 years of an open-source quantum chemistry project
Qiming Sun, Matthew R Hermes, Xiaojie Wu +100
Over the past decade, the Python-based Simulations of Chemistry Framework (PySCF) has developed into a widely used open-source platform for electronic structure theory and quantum…
Implementation of the multigrid Gaussian-Plane-Wave algorithm with GPU acceleration in PySCF
Rui Li, Xing Zhang, Qiming Sun +3
We introduce a GPU-accelerated multigrid Gaussian-Plane-Wave density fitting (FFTDF) approach for efficient Fock builds and nuclear gradient evaluations within Kohn-Sham density fu…
Classical computational simulation of the FeMo-cofactor model to chemical accuracy and its implications
Huanchen Zhai, Chenghan Li, Xing Zhang +3
We use classical computational methods to estimate the ground-state energy to chemical accuracy in a model of the FeMo-cofactor of nitrogenase which is widely studied as a target o…
Predictive Free Energy Simulations Through Hierarchical Distillation of Quantum Hamiltonians
Chenghan Li, Garnet Kin-Lic Chan
Obtaining the free energies of condensed phase chemical reactions remains computationally prohibitive for high-level quantum mechanical methods. We introduce a hierarchical machine…
Reactive Chemistry at Unrestricted Coupled Cluster Level: High-throughput Calculations for Training Machine Learning Potentials
Alice E. A. Allen, Rui Li, Sakib Matin +8
Accurately modeling chemical reactions at the atomistic level requires high-level electronic structure theory due to the presence of unpaired electrons and the need to properly des…
Accurate crystal field Hamiltonians of single-ion magnets at mean-field cost
Linqing Peng, Shuanglong Liu, Xing Zhang +4
The effective crystal field Hamiltonian provides the key description of the electronic properties of single-ion magnets, but obtaining its parameters from ab initio computation is…
Exploring the design space of machine-learning models for quantum chemistry with a fully differentiable framework
Divya Suman, Jigyasa Nigam, Sandra Saade +5
Traditional atomistic machine learning (ML) models serve as surrogates for quantum mechanical (QM) properties, predicting quantities such as dipole moments and polarizabilities, di…
Towards Excitations and Dynamical Quantities in Correlated Lattices with Density Matrix Embedding Theory
Shuoxue Li, Chenghan Li, Huanchen Zhai +1
Density matrix embedding theory (DMET) provides a framework to describe ground-state expectation values in strongly correlated systems, but its extension to dynamical quantities is…
Efficient Implementation of the Random Phase Approximation with Domain-based Local Pair Natural Orbitals
Yu Hsuan Liang, Xing Zhang, Garnet Kin-Lic Chan +2
We present an efficient implementation of the random phase approximation (RPA) for molecular systems within the domain-based local pair natural orbital (DLPNO) framework. With opti…
General Quantum Alchemical Free Energy Simulations via Hamiltonian Interpolation
Chenghan Li, Xing Zhang, Garnet Kin-Lic Chan
We present an implementation of alchemical free energy simulations at the quantum mechanical level by directly interpolating the electronic Hamiltonian. The method is compatible wi…
Accurate QM/MM Molecular Dynamics for Periodic Systems in \textsc{GPU4PySCF} with Applications to Enzyme Catalysis
Chenghan Li, Garnet Kin-Lic Chan
We present an implementation of the quantum mechanics/molecular mechanics (QM/MM) method for periodic systems using GPU accelerated QM methods, a distributed multipole formulation…
Introducing GPU-acceleration into the Python-based Simulations of Chemistry Framework
Rui Li, Qiming Sun, Xing Zhang +1
We introduce the first version of GPU4PySCF, a module that provides GPU acceleration of methods in PySCF. As a core functionality, this provides a GPU implementation of two-electro…
Performant Automatic Differentiation of Local Coupled Cluster Theories: Response Properties and Ab Initio Molecular Dynamics
Xing Zhang, Chenghan Li, Hong-Zhou Ye +2
In this work, we introduce a differentiable implementation of the local natural orbital coupled cluster (LNOCC) method within the automatic differentiation framework of the PySCFAD…
Image Super-resolution Inspired Electron Density Prediction
Chenghan Li, Or Sharir, Shunyue Yuan +1
Drawing inspiration from the domain of image super-resolution, we view the electron density as a 3D grayscale image and use a convolutional residual network to transform a crude an…
Multi-site Reaction Dynamics Through Multi-fragment Density Matrix Embedding
Chenghan Li, Junjie Yang, Xing Zhang +1
The practical description of disordered chemical reactions, where reactions involve multiple species at multiple sites, is presently challenge using correlated electronic structure…