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Full-Text Articles in Physics

Understanding Three-Body Interactions In Hexagonal Close Packed Solid He-4, Ashleigh Locke Barnes May 2017

Understanding Three-Body Interactions In Hexagonal Close Packed Solid He-4, Ashleigh Locke Barnes

Doctoral Dissertations

The ground state properties of hexagonal close packed (hcp) solid 4He [He-4] are dominated by large atomic zero point motions which make the primary contribution to the solid’s low-temperature Debye-Waller (DW) factors. Preliminary investigations have also suggested that three-body interactions can play an important role in this system, particularly at higher densities. However, due to their computational cost, these interactions are not generally incorporated into theoretical models of solid 4He [He-4]. In order to accurately treat both zero point motion and three-body interactions, we have developed a perturbative treatment in which the three-body energy is added as ...


Qsats: Mpi-Driven Quantum Simulations Of Atomic Solids At Zero Temperature, R. Hinde Dec 2010

Qsats: Mpi-Driven Quantum Simulations Of Atomic Solids At Zero Temperature, R. Hinde

Robert Hinde

We describe QSATS, a parallel code for performing variational path integral simulations of the quantum mechanical ground state of monatomic solids. QSATS is designed to treat Boltzmann quantum solids, in which individual atoms are permanently associated with distinguishable crystal lattice sites and undergo large-amplitude zero-point motions around these sites. We demonstrate the capabilities of QSATS by using it to compute the total energy and potential energy of hexagonal close packed solid 4He at the density 4.61421 x 10-3 a0-3.


Fpga Acceleration Of A Quantum Monte Carlo Application, Robert Hinde Dec 2007

Fpga Acceleration Of A Quantum Monte Carlo Application, Robert Hinde

Robert Hinde

Quantum Monte Carlo methods enable us to determine the ground-state properties of atomic or molecular clusters. Here, we present a reconfigurable computing architecture using Field Programmable Gate Arrays (FPGAs) to accelerate two computationally intensive kernels of a Quantum Monte Carlo (QMC) application applied to N-body systems. We focus on two key kernels of the QMC application: acceleration of potential energy and wave function calculations. We compare the performance of our application on two reconfigurable platforms. Firstly, we use a dual-processor 2.4 GHz Intel Xeon augmented with two reconfigurable development boards consisting of Xilinx Virtex-II Pro FPGAs. Using this platform ...


Population Size Bias In Descendant-Weighted Diffusion Quantum Monte Carlo Simulations, G. Lee Warren, Robert J. Hinde Jan 2006

Population Size Bias In Descendant-Weighted Diffusion Quantum Monte Carlo Simulations, G. Lee Warren, Robert J. Hinde

Chemistry Publications and Other Works

We consider the influence of population size on the accuracy of diffusion quantum Monte Carlo simulations that employ descendant weighting or forward walking techniques to compute expectation values of observables that do not commute with the Hamiltonian. We show that for a simple model system, the d-dimensional isotropic harmonic oscillator, the population size must increase rapidly with d in order to ensure that the simulations produce accurate results. When the population size is too small, expectation values computed using descendant-weighted diffusion quantum Monte Carlo simulations exhibit significant systematic biases.


Variational Path Integral Simulations Using Discretized Coordinates, Robert Hinde Dec 2005

Variational Path Integral Simulations Using Discretized Coordinates, Robert Hinde

Robert Hinde

We describe a variational path integral simulation algorithm for quantum Monte Carlo studies of many-body systems in which particles are restricted to occupy sites on a regular simple cubic lattice with lattice constant s, and discuss the algorithm’s potential computational benefits. Application of the algorithm to the weakly bound cluster Ne3 shows that accurate coordinate-space observables for this system can be computed using lattice constants as large as s = 0.2 a0.


Population Size Bias In Descendant-Weighted Diffusion Quantum Monte Carlo Simulations, G. Lee Warren, Robert Hinde Dec 2005

Population Size Bias In Descendant-Weighted Diffusion Quantum Monte Carlo Simulations, G. Lee Warren, Robert Hinde

Robert Hinde

We consider the influence of population size on the accuracy of diffusion quantum Monte Carlo simulations that employ descendant weighting or forward walking techniques to compute expectation values of observables that do not commute with the Hamiltonian. We show that for a simple model system, the d-dimensional isotropic harmonic oscillator, the population size must increase rapidly with d in order to ensure that the simulations produce accurate results. When the population size is too small, expectation values computed using descendant-weighted diffusion quantum Monte Carlo simulations exhibit significant systematic biases.