George I. Fann

High performance computational chemistry: An overview of NWChem a distributed parallel application☆

NWChem is the software package for computational chemistry on massively parallel computing systems developed by the High Performance Computational Chemistry Group for the Environmental Molecular Sciences Laboratory. The software provides a variety of modules for quantum mechanical and classical mechanical simulation. This article describes the design and some implementation details of the overall NWChem architecture. The architecture facilitates rapid development and portability of fully distributed application modules. We also delineate some of the functionality within NWChem and show performance of a few of the modules within NWChem.

Multiresolution quantum chemistry: Basic theory and initial applications

We describe a multiresolution solver for the all-electron local density approximation Kohn-Sham equations for general polyatomic molecules. The resulting solutions are obtained to a user-specified precision and the computational cost of applying all operators scales linearly with the number of parameters. The construction and use of separated forms for operators (here, the Greens functions for the Poisson and bound-state Helmholtz equations) enable practical computation in three and higher dimensions. Initial applications include the alkali-earth atoms down to strontium and the water and benzene molecules.

Feature Selection and Classification of Hyperspectral Images With Support Vector Machines

Hyperspectral images consist of large number of bands which require sophisticated analysis to extract. One approach to reduce computational cost, information representation, and accelerate knowledge discovery is to eliminate bands that do not add value to the classification and analysis method which is being applied. In particular, algorithms that perform band elimination should be designed to take advantage of the structure of the classification method used. This letter introduces an embedded-feature-selection (EFS) algorithm that is tailored to operate with support vector machines (SVMs) to perform band selection and classification simultaneously. We have successfully applied this algorithm to determine a reasonable subset of bands without any user-defined stopping criteria on some sample AVIRIS images; a problem occurs in benchmarking recursive-feature-elimination methods for the SVMs.

Multiresolution quantum chemistry in multiwavelet bases: Hartree–Fock exchange

In a previous study we reported an efficient, accurate multiresolution solver for the Kohn-Sham self-consisitent field (KS-SCF) method for general polyatomic molecules. This study presents an efficient numerical algorithm to evalute Hartree-Fock (HF) exchange in the multiresolution SCF method to solve the HF equations. The algorithm employs fast integral convolution with the Poission kernel in the nonstandard form, screening the sparse multiwavelet representation to compute results of the integral operator only where required by the nonlocal exchange operator. Localized molecular obitals are used to attain near linear scaling. Results for atoms and molecules demonstrate reliable precision and speed. Calculations for small water clusters demonstrate a total cost to compute the HF exchange potential for all n(occ) occpuied MOs scaling as O(n(occ) (1.5)).

Multiresolution Quantum Chemistry in Multiwavelet Bases: Analytic Derivatives for Hartree-Fock and Density Functional Theory

An efficient and accurate analytic gradient method is presented for Hartree-Fock and density functional calculations using multiresolution analysis in multiwavelet bases. The derivative is efficiently computed as an inner product between compressed forms of the density and the differentiated nuclear potential through the Hellmann-Feynman theorem. A smoothed nuclear potential is directly differentiated, and the smoothing parameter required for a given accuracy is empirically determined from calculations on six homonuclear diatomic molecules. The derivatives of N2 molecule are shown using multiresolution calculation for various accuracies with comparison to correlation consistent Gaussian-type basis sets. The optimized geometries of several molecules are presented using Hartree-Fock and density functional theory. A highly precise Hartree-Fock optimization for the H2O molecule produced six digits for the geometric parameters.

Multiresolution quantum chemistry in multiwavelet bases

Multiresolution analysis in multiwavelet bases is being investigated as an alternative computational framework for molecular electronic structure calculations. The features that make it attractive include an orthonormal basis, fast algorithms with guaranteed precision and sparse representations of many operators (e.g., Green functions). In this paper, we discuss the multiresolution formulation of quantum chemistry including application to density functional theory and developments that make practical computation in three and higher dimensions.

Singular operators in multiwavelet bases

We review some recent results on multiwavelet methods for solving integral and partial differential equations and present an efficient representation of operators using discontinuous multiwavelet bases, including the case for singular integral operators. Numerical calculus using these representations produces fast O(N) methods for multiscale solution of integral equations when combined with low separation rank methods. Using this formulation, we compute the Hilbert transform and solve the Poisson and SchrA¶dinger equations. For a fixed order of multiwavelets and for arbitrary but finite- precision computations, the computational complexity is O(N). The computational structures are similar to fast multipole methods but are more generic in yielding fast O(N) algorithm development.

Computational nuclear quantum many-body problem: The UNEDF project

The UNEDF project was a large-scale collaborative effort that applied high-performance computing to the nuclear quantum many-body problem. The primary focus of the project was on constructing, validating, and applying an optimized nuclear energy density functional, which entailed a wide range of pioneering developments in microscopic nuclear structure and reactions, algorithms, high-performance computing, and uncertainty quantification. UNEDF demonstrated that close associations among nuclear physicists, mathematicians, and computer scientists can lead to novel physics outcomes built on algorithmic innovations and computational developments. This review showcases a wide range of UNEDF science results to illustrate this interplay.

Deformed Coordinate-Space Hartree-Fock-Bogoliubov Approach to Weakly Bound Nuclei and Large Deformations

The coordinate space formulation of the Hartree-Fock-Bogoliubov (HFB) method enables self-consistent treatment of mean field and pairing in weakly bound systems whose properties are affected by the particle continuum space. Of particular interest are neutron-rich, deformed drip-line nuclei which can exhibit novel properties associated with neutron skin. To describe such systems theoretically, we developed an accurate 2D lattice Skyrme-HFB solver HFB-AX based on B-splines. Compared to previous implementations, we made a number of improvements aimed at boosting the solvers performance. These include: explicit imposition of axiality and space inversion, use of the modified Broydens method to solve self-consistent equations, and a partial parallelization of the code. HFB-AX has been benchmarked against other HFB solvers, both spherical and deformed, and the accuracy of the B-spline expansion was tested by employing the multi-resolution wavelet method. Illustrative calculations are carried out for stable and weakly bound nuclei at spherical and very deformed shapes, including constrained fission pathways. In addition to providing new physics insights, HFB-AX can serve as a useful tool to assess the reliability and applicability of coordinate-space and configuration-space HFB solvers, both existing and in development.

MADNESS: A Multiresolution, Adaptive Numerical Environment for Scientific Simulation

MADNESS (multiresolution adaptive numerical environment for scientific simulation) is a high-level software environment for solving integral and differential equations in many dimensions that uses adaptive and fast harmonic analysis methods with guaranteed precision that are based on multiresolution analysis and separated representations. Underpinning the numerical capabilities is a powerful petascale parallel programming environment that aims to increase both programmer productivity and code scalability. This paper describes the features and capabilities of MADNESS and briefly discusses some current applications in chemistry and several areas of physics.