QMCPACK: Advances in the development, efficiency, and application of auxiliary field and real-space variational and diffusion quantum Monte Carlo.

We review recent advances in the capabilities of the open source ab initio Quantum Monte Carlo (QMC) package QMCPACK and the workflow tool Nexus used for greater efficiency and reproducibility. The auxiliary field QMC (AFQMC) implementation has been greatly expanded to include k-point symmetries, tensor-hypercontraction, and accelerated graphical processing unit (GPU) support. These scaling and memory reductions greatly increase the number of orbitals that can practically be included in AFQMC calculations, increasing the accuracy. Advances in real space methods include techniques for accurate computation of bandgaps and for systematically improving the nodal surface of ground state wavefunctions. Results of these calculations can be used to validate application of more approximate electronic structure methods, including GW and density functional based techniques. To provide an improved foundation for these calculations, we utilize a new set of correlation-consistent effective core potentials (pseudopotentials) that are more accurate than previous sets; these can also be applied in quantum-chemical and other many-body applications, not only QMC. These advances increase the efficiency, accuracy, and range of properties that can be studied in both molecules and materials with QMC and QMCPACK.

Accurate Predictions of Electron Binding Energies of Dipole-Bound Anions via Quantum Monte Carlo Methods.

Neutral molecules with sufficiently large dipole moments can bind electrons in diffuse nonvalence orbitals with most of their charge density far from the nuclei, forming so-called dipole-bound anions. Because long-range correlation effects play an important role in the binding of an excess electron and overall binding energies are often only on the order of 10s-100s of wave numbers, predictively modeling dipole-bound anions remains a challenge. Here, we demonstrate that quantum Monte Carlo methods can accurately characterize molecular dipole-bound anions with near-threshold dipole moments. We also show that correlated sampling Auxiliary Field Quantum Monte Carlo is particularly well-suited for resolving the fine energy differences between the neutral and anionic species. These results shed light on the fundamental limitations of quantum Monte Carlo methods and pave the way toward using them for the study of weakly bound species that are too large to model using traditional electron structure methods.

QMCPACK: an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids.

QMCPACK is an open source quantum Monte Carlo package for ab initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wavefunctions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary-field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performance computing architectures, including multicore central processing unit and graphical processing unit systems. We detail the program's capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://qmcpack.org.

Rapid, on-site identification of explosives in nanoliter droplets using a UV reflected fiber optic sensor.

A portable UV (190-400 nm) spectrophotometric based reflected fiber optic sensor system is presented for the on-site detection and identification of explosives. A reflected fiber optic sensor for explosives analysis was developed, with low sample consumption (20-100 nL) and a wide concentration quantification range (1.1-250 mg L(-1)). Seven common explosives [pentaerythritol tetranitrate (PETN), trinitrophenylmethylnitramine (CE), trinitrotoluene (TNT), dinitrotoluene (DNT), picric acid (PA), cyclotetramethylenetetranitramine (HMX), cyclotrimethylenetrinitramine (RDX)] and a PETN-RDX mixture (to simulate the Semtex used in many terrorist bombings) were quantitatively analyzed and identified by the proposed system in less than 3s per test, with limits of detection (LOD) of 0.3 mg L(-1). Due to chemical interference problems in the UV wavelengths range, a novel feature matching algorithm (FMA) was proposed for explosive identification, which was proved to have higher specificity and better anti-interference ability. Real post-blast debris samples were analyzed by the proposed method, and the results were validated against an LC/MS/MS method. The rapid, cost-effective detection with low sample consumption and wide applicability achieved by this system is highly suitable for homeland security on-site applications, such as rapid sample screening in post-blast debris.