Anouar Benali

Application of Diffusion Monte Carlo to Materials Dominated by van der Waals Interactions.

van der Waals forces are notoriously difficult to account for from first principles. We have performed extensive calculations to assess the usefulness and validity of diffusion quantum Monte Carlo when predicting van der Waals forces. We present converged results for noble gas solids and clusters, archetypical van der Waals dominated systems, as well as the highly relevant π-π stacking supramolecular complex: DNA + intercalating anticancer drug ellipticine. Analysis of the calculated binding energies underscores the existence of significant interatomic many-body contributions.

Phase stability of TiO2 polymorphs from diffusion Quantum Monte Carlo

Titanium dioxide, TiO

Quantum Monte Carlo analysis of a charge ordered insulating antiferromagnet: The Ti4O7 Magneli phase

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

, has multiple applications in catalysis, energy conversion and memristive devices because of its electronic structure. Most of these applications utilize the naturally existing phases: rutile, anatase and brookite. Despite the simple form of TiO

Global-view coefficients: a data management solution for parallel quantum Monte Carlo applications

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Benchmarks and Reliable DFT Results for Spin Gaps of Small Ligand Fe(II) Complexes

and its wide uses, there is long-standing disagreement between theory and experiment on the energetic ordering of these phases that has never been resolved. We present the first analysis of phase stability at zero temperature using the highly accurate many-body fixed node diffusion Quantum Monte Carlo (QMC) method. We also include the effects of temperature by calculating the Helmholtz free energy including both internal energy and vibrational contributions from density functional perturbation theory based quasi harmonic phonon calculations. Our QMC calculations find that anatase is the most stable phase at zero temperature, consistent with many previous mean-field calculations. However, at elevated temperatures, rutile becomes the most stable phase. For all finite temperatures, brookite is always the least stable phase.

Optimization and Parallelization of B-Spline Based Orbital Evaluations in QMC on Multi/Many-Core Shared Memory Processors

The Magnéli phase Ti4O7 is an important transition metal oxide with a wide range of applications because of its interplay between charge, spin, and lattice degrees of freedom. At low temperatures, it has non-trivial magnetic states very close in energy, driven by electronic exchange and correlation interactions. We have examined three low-lying states, one ferromagnetic and two antiferromagnetic, and calculated their energies as well as Ti spin moment distributions using highly accurate quantum Monte Carlo methods. We compare our results to those obtained from density functional theory-based methods that include approximate corrections for exchange and correlation. Our results confirm the nature of the states and their ordering in energy, as compared with density-functional theory methods. However, the energy differences and spin distributions differ. A detailed analysis suggests that non-local exchange-correlation functionals, in addition to other approximations such as LDA+U to account for correlations, are needed to simultaneously obtain better estimates for spin moments, distributions, energy differences and energy gaps.

Nature of Interlayer Binding and Stacking of sp–sp2 Hybridized Carbon Layers: A Quantum Monte Carlo Study

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 programs capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://qmcpack.org.

Excitation energies from diffusion Monte Carlo using selected configuration interaction nodes

Quantum Monte Carlo (QMC) applications perform simulation with respect to an initial state of the quantum mechanical system, which is often captured by using a cubic B‐spline basis. This representation is stored as a read‐only table of coefficients and accesses to the table are generated at random as part of the Monte Carlo simulation. Current QMC applications, such as QWalk and QMCPACK, replicate this table at every process or node, which limits scalability because increasing the number of processors does not enable larger systems to be run. We present a partitioned global address space approach to transparently managing this data using Global Arrays in a manner that allows the memory of multiple nodes to be aggregated. We develop an automated data management system that significantly reduces communication overheads, enabling new capabilities for QMC codes. Experimental results with QWalk and QMCPACK demonstrate the effectiveness of the data management system. Copyright

Embracing a new era of highly efficient and productive quantum Monte Carlo simulations

All-electron fixed-node diffusion Monte Carlo provides benchmark spin gaps for four Fe(II) octahedral complexes. Standard quantum chemical methods (semilocal DFT and CCSD(T)) fail badly for the energy difference between their high- and low-spin states. Density-corrected DFT is both significantly more accurate and reliable and yields a consistent prediction for the Fe-Porphyrin complex.