This work involves studying and developing new algorithms for molecular numerical integration used for density functional theory and new algorithms for Hartree-Fock method. -- New insight about molecular numerical integration is presented through a detailed study of the performance of some of the well known grids in addition to our implementation of the most recently developed MultiExp grid. A comprehensive study of numerical integration was conducted by evaluating several molecular properties: number of electrons, dipole moment, potential energy, and Coulomb repulsion energy using fifteen grids including a large benchmark grid. The standard grid (SG-1) and a slightly modified version of the Treutler and Alhrichs (TA) grid performed reasonably well. The MultiExp grid, which is more efficient, was studied as well and found to be less accurate. -- Studying large molecules using Hartree-Fock method is a challenge both in terms of CPU time and memory requirements. However, there is a high demand to perform quantum chemical calculations for large molecules. Projection from a smaller basis set to a larger basis set was studied in detail. It was found that projection from the STO-3G basis set to the 6-31G basis set performed well. Projection was used to develop a new version of a divide and conquer algorithm. Our divide and conquer algorithm was used to calculate the protonation energy for a series of peptides. Algorithms to skip calculating two-electron integrals of zero or negligible values are presented in addition to an algorithm to generate a better initial guess.
This work involves studying and developing new algorithms for molecular numerical integration used for density functional theory and new algorithms for Hartree-Fock method. -- New insight about molecular numerical integration is presented through a detailed study of the performance of some of the well known grids in addition to our implementation of the most recently developed MultiExp grid. A comprehensive study of numerical integration was conducted by evaluating several molecular properties: number of electrons, dipole moment, potential energy, and Coulomb repulsion energy using fifteen grids including a large benchmark grid. The standard grid (SG-1) and a slightly modified version of the Treutler and Alhrichs (TA) grid performed reasonably well. The MultiExp grid, which is more efficient, was studied as well and found to be less accurate. -- Studying large molecules using Hartree-Fock method is a challenge both in terms of CPU time and memory requirements. However, there is a high demand to perform quantum chemical calculations for large molecules. Projection from a smaller basis set to a larger basis set was studied in detail. It was found that projection from the STO-3G basis set to the 6-31G basis set performed well. Projection was used to develop a new version of a divide and conquer algorithm. Our divide and conquer algorithm was used to calculate the protonation energy for a series of peptides. Algorithms to skip calculating two-electron integrals of zero or negligible values are presented in addition to an algorithm to generate a better initial guess.
Evaluating the Coulomb interaction remains a fundamental computational bottleneck in electronic structure theory, dictating the scaling and efficiency of quantum chemical simulations. While recent advancements in graphics processing units (GPUs) offer immense theoretical peak performance, translating traditional, memory-intensive CPU algorithms for evaluating electron repulsion integrals to GPU architectures presents significant challenges due to memory bandwidth limitations and warp divergence. This thesis presents the development of algorithms to efficiently evaluate Coulomb interactions across diverse chemical systems. Chapter 2 describes the GPU implementation of Coulomb interaction for molecular systems at Hartree-Fock level of theory. Chapter 3 shows how multigrid Gaussian-Plane-Wave algorithm can better utilize GPU compute performance by a two-level parallelization scheme and grid-based screening of orbital pairs in the real space. Chapter 4 illustrates the issues of the original modified Coulomb potential from GFN-xTB in periodic systems, and the effectiveness of a new generalized Ewald summation scheme for the potential in X23 molecular crystal dataset and a range of prototypical bulk semiconductors.
We study the efficiency, precision and accuracy of all-electron variational and diffusion quantum Monte Carlo calculations using Slater basis sets. Starting from wave functions generated by Hartree-Fock and density functional theory, we describe an algorithm to enforce the electron-nucleus cusp condition by linear projection. For the 55 molecules in the G2 set, the diffusion quantum Monte Carlo calculations recovers an average of 95% of the correlation energy and reproduces bond energies to a mean absolute deviation of 3.2 kcal/mol. Comparing the individual total energies with essentially exact values, we investigate the error cancellation in atomization and chemical reaction path energies, giving additional insight into the sizes of nodal surface errors.
We resume the recent successes of the grid-based tensor numerical methods and discuss their prospects in real-space electronic structure calculations. These methods, based on the low-rank representation of the multidimensional functions and integral operators, first appeared as an accurate tensor calculus for the 3D Hartree potential using 1D complexity operations, and have evolved to entirely grid-based tensor-structured 3D Hartree-Fock eigenvalue solver. It benefits from tensor calculation of the core Hamiltonian and two-electron integrals (TEI) in O(n log n) complexity using the rank-structured approximation of basis functions, electron densities and convolution integral operators all represented on 3D n × n × n Cartesian grids. The algorithm for calculating TEI tensor in a form of the Cholesky decomposition is based on multiple factorizations using algebraic 1D "density fitting" scheme, which yield an almost irreducible number of product basis functions involved in the 3D convolution integrals, depending on a threshold ε > 0. The basis functions are not restricted to separable Gaussians, since the analytical integration is substituted by high-precision tensor-structured numerical quadratures. The tensor approaches to post-Hartree-Fock calculations for the MP2 energy correction and for the Bethe-Salpeter excitation energies, based on using low-rank factorizations and the reduced basis method, were recently introduced. Another direction is towards the tensor-based Hartree-Fock numerical scheme for finite lattices, where one of the numerical challenges is the summation of electrostatic potentials of a large number of nuclei. The 3D grid-based tensor method for calculation of a potential sum on a L × L × L lattice manifests the linear in L computational work, O(L), instead of the usual O(L(3) log L) scaling by the Ewald-type approaches.
In spite of recent advances, quantum computers are expected to be sufficiently noisy in the coming few years to the extent of limiting quantum chemical calculations to relatively small number of orbitals. However, even with reasonable quality single particle basis sets, small active spaces with limited orbitals can result in a significant fraction of correlation energy being lost, motivating the design of moderate quality qubit-efficient basis sets for quantum algorithms. We begin by reoptimizing the existing minimal basis sets using a genetic algorithm-inspired approach in conjunction with aggressive refinement strategies, and generate modified minimal basis sets (MSTO-kG basis; k = 2-11) for atoms from H through F. The ground state energies of H through F using our MSTO bases at FCI level of theory yield ground state energies that are comparable or sometimes even lower than those obtained using 6-31G basis sets. In the case of Li, the MSTO bases surpass the performance of cc-pVQZ bases. Thus, we obtain better atomic energies with same number of qubits relative to STO bases, and better/comparable energies with fewer qubits relative to higher quality bases. In the case of molecules, H2 performs poorly; a finding that is consistent with an earlier work in literature. For other molecules, Li2, C2, LiH, BeH and BeH2, the FCI results (except C2 for which we employ CISD) from our bases are comparable to/outperform those from 6-31G basis. Finally, we compare the resources required between different bases and find that MSTO bases yield better energies than the competing basis sets while incurring fewer qubits and two-qubit gates with VQE, QPE, and HHL. The logical T-gate counts are also found to be considerably lower for QPE and HHL respectively. Overall, our work paves way for more accurate yet less qubit-hungry quantum chemical calculations using near-term quantum computers.
Modern videogames place increasing demands on the computational and graphical hardware, leading to novel architectures that have great potential in the context of high performance computing and molecular simulation. We demonstrate that Graphical Processing Units (GPUs) can be used very efficiently to calculate two-electron repulsion integrals over Gaussian basis functions [Formula: see text] the first step in most quantum chemistry calculations. A benchmark test performed for the evaluation of approximately 10(6) (ss|ss) integrals over contracted s-orbitals showed that a naïve algorithm implemented on the GPU achieves up to 130-fold speedup over a traditional CPU implementation on an AMD Opteron. Subsequent calculations of the Coulomb operator for a 256-atom DNA strand show that the GPU advantage is maintained for basis sets including higher angular momentum functions.
Determining properties of molecules and materials is one of the premier applications of quantum computing. A major question in the thesis is: how might we use long- and near-term quantum computers to solve problems of chemical interest? First, we give an overview of the standard model in electronic structure theory. Electronic structure methods have been improved significantly in the last decades; however, it is still a non-trivial task to fit experimental results for complex molecular systems. Second, we introduce quantum computation and quantum algorithms as an alternative device to solve the electronic structure problem. In the remaining part of the thesis, we describe the research projects. The thesis covers two (rather different) research directions: software and hardware projects. For the software part, we contribute with two new algorithms: Phase-Estimation Interval Target Energy Readout (PHILTER) and Recursive Variational Series Estimation (RVSE), where both are designed to be run on a quantum digital computer and extract materials and molecular properties. The PHILTER algorithm is a modification of the Quantum Phase Estimation and is designed to compute excited state energies within a target energy-interval for cases where good approximations for the states in the target energy-interval are either unknown or hard to prepare. For the RVSE algorithm, we pose the question: how might we use imperfect near-term quantum computers to solve problems of practical value? In this work, we introduce a method to compute expectation values of general functions of a Hamiltonian with respect to an input state using low depth quantum circuits suitable for noisy intermediate-scale quantum computers. For the hardware part, we propose a new chemical quantum computer by using molecular electronics as a basis for quantum computing. In this work, we pose the question: can scattering of electrons in molecules produce quantum gates? We construct one-qubit gates using one-electron scattering in molecules, and two-qubit controlled-phase gates using electron-electron scattering along metallic leads. We show initial applications of the framework by illustrating one-qubit gates using the molecular electronic structure of molecular hydrogen as a baseline model.