Exploring Locality in Molecular Dirac-Coulomb-Breit Calculations: A Perspective
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Chemistry↗
Engineering topics
Sun, Qiming
Publications and source records attributed to Sun, Qiming.
Scalar Breit interaction for molecular calculations
Variational treatment of the Dirac–Coulomb–Gaunt or Dirac–Coulomb–Breit two-electron interaction at the Dirac–Hartree–Fock level is the starting point of high-accuracy four-component calculations of atomic and molecular systems. In this work, we introduce, for the first time, the scalar Hamiltonians derived from the Dirac–Coulomb–Gaunt and Dirac–Coulomb–Breit operators based on spin separation in the Pauli quaternion basis. While the widely used spin-free Dirac–Coulomb Hamiltonian includes only the direct Coulomb and exchange terms that resemble nonrelativistic two-electron interactions, the scalar Gaunt operator adds a scalar spin–spin term. The spin separation of the gauge operator gives rise to an additional scalar orbit-orbit interaction in the scalar Breit Hamiltonian. Benchmark calculations of Au n (n = 2–8) show that the scalar Dirac–Coulomb–Breit Hamiltonian can capture 99.99% of the total energy with only 10% of the computational cost when real-valued arithmetic is used, compared to the full Dirac–Coulomb–Breit Hamiltonian. In conclusion, the scalar relativistic formulation developed in this work lays the theoretical foundation for the development of high-accuracy, low-cost correlated variational relativistic many-body theory.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Efficient evaluation of the Breit operator in the Pauli spinor basis
The frequency-independent Coulomb–Breit operator gives rise to the most accurate treatment of two-electron interaction in the non-quantum-electrodynamics regime. The Breit interaction in the Coulomb gauge consists of magnetic and gauge contributions. The high computational cost of the gauge term limits the application of the Breit interaction in relativistic molecular calculations. In this work, we apply the Pauli component integral–density matrix contraction scheme for gauge interaction with a maximum spin- and component separation scheme. We also present two different computational algorithms for evaluating gauge integrals. One is the generalized Obara–Saika algorithm, where the Laplace transformation is used to transform the gauge operator into Gaussian functions and the Obara–Saika recursion is used for reducing the angular momentum. The other algorithm is the second derivative of Coulomb interaction evaluated with Rys-quadrature. This work improves the efficiency of performing Dirac–Hartree–Fock with the variational treatment of Breit interaction for molecular systems. In conclusion, we use this formalism to examine relativistic trends in the Periodic Table and analyze the relativistic two-electron interaction contributions in heavy-element complexes.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Relativistic self-consistent G W : Exact two-component formalism with one-electron approximation for solids
We present a formulation of relativistic self-consistent GW for solids based on the exact two-component formalism with one-electron approximation (X2C1e) and nonrelativistic Coulomb interactions. Our theory allows us to study scalar relativistic effects, spin-orbit coupling, and the interplay of relativistic effects with electron correlation without adjustable parameters. Our all-electron implementation is fully ab initio and does not require a pseudopotential constructed from atomic calculations. We examine the effect of the X2C1e approximation by comparison to the established four-component formalism and reach an excellent agreement. The simplicity of X2C1e enables the construction of higher order theories, such as embedding theories, on top of perturbative calculations.
36 MATERIALS SCIENCE↗
MLL1 is regulated by KSHV LANA and is important for virus latency
Abstract Mixed lineage leukemia 1 (MLL1) is a histone methyltransferase. Kaposi's sarcoma-associated herpesvirus (KSHV) is a leading cause of malignancy in AIDS. KSHV latently infects tumor cells and its genome is decorated with epigenetic marks. Here, we show that KSHV latency-associated nuclear antigen (LANA) recruits MLL1 to viral DNA where it establishes H3K4me3 modifications at the extensive KSHV terminal repeat elements during primary infection. LANA interacts with MLL1 complex members, including WDR5, integrates into the MLL1 complex, and regulates MLL1 activity. We describe the 1.5-Å crystal structure of N-terminal LANA peptide complexed with MLL1 complex member WDR5, which reveals a potential regulatory mechanism. Disruption of MLL1 expression rendered KSHV latency establishment highly deficient. This deficiency was rescued by MLL1 but not by catalytically inactive MLL1. Therefore, MLL1 is LANA regulable and exerts a central role in virus infection. These results suggest broad potential for MLL1 regulation, including by non-host factors.
Tan, Min↗
Efficient Four-Component Dirac–Coulomb–Gaunt Hartree–Fock in the Pauli Spinor Representation
Four-component Dirac Hartree--Fock is an accurate mean-field method for treating molecular systems where relativistic effects are important. However, the computational cost and complexity of the two-electron interaction makes this method less common, even though we can consider the Dirac Hartree--Fock Hamiltonian the ``ground truth" of electronic structure, barring explicit quantum-electrodynamical effects. Being able to calculate these effects is then vital to the design of lower scaling methods for accurate predictions in computational spectroscopy and properties of heavy element complexes that must include relativistic effects for even qualitative accuracy. In this work, we present a Pauli quaternion formalism of maximal component- and spin-separation for computing the Dirac-Coulomb-Gaunt Hartree-Fock ground state, with a minimal floating-point-operation count algorithm. Furthermore, this approach also allows one to explicitly separate different spin physics from the two-body interactions, such as spin-free, spin-orbit, and the spin-spin contributions. Additionally, we use this formalism to examine relativistic trends in the periodic table, and analyze the basis set dependence of atomic gold and gold dimer systems.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Machine learning Frenkel Hamiltonian parameters to accelerate simulations of exciton dynamics
In this manuscript, we develop multiple machine learning (ML) models to accelerate a scheme for parameterizing site-based models of exciton dynamics from all-atom configurations of condensed phase sexithiophene systems. This scheme encodes the details of a system’s specific molecular morphology in the correlated distributions of model parameters through the analysis of many single-molecule excited-state electronic-structure calculations. These calculations yield excitation energies for each molecule in the system and the network of pair-wise intermolecular electronic couplings. In this work, we demonstrate that the excitation energies can be accurately predicted using a kernel ridge regression (KRR) model with Coulomb matrix featurization. We present two ML models for predicting intermolecular couplings. The first one utilizes a deep neural network and bi-molecular featurization to predict the coupling directly, which we find to perform poorly. The second one utilizes a KRR model to predict unimolecular transition densities, which can subsequently be analyzed to compute the coupling. We find that the latter approach performs excellently, indicating that an effective, generalizable strategy for predicting simple bimolecular properties is through the indirect application of ML to predict higher-order unimolecular properties. Such an approach necessitates a much smaller feature space and can incorporate the insight of well-established molecular physics.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Recent developments in the PySCF program package
PySCF is a Python-based general-purpose electronic structure platform that supports first-principles simulations of molecules and solids as well as accelerates the development of new methodology and complex computational workflows. Here, we explain the design and philosophy behind PySCF that enables it to meet these twin objectives. With several case studies, we show how users can easily implement their own methods using PySCF as a development environment. We then summarize the capabilities of PySCF for molecular and solid-state simulations. Finally, we describe the growing ecosystem of projects that use PySCF across the domains of quantum chemistry, materials science, machine learning, and quantum information science.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗