Quantum Monte Carlo Using Multicore Processors: Enabling Simulations in Inhomogeneous Environments

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Developing an understanding of, and a predictive capability for, strongly correlated electron systems (SCES), is a rapidly evolving field that relies critically on faster computation for continued progress. SCES form the basis of crucial materials capabilities, including high temperature superconductivity, nuclear fuels, new classes of thermoelectrics, and the exotic and promising behavior seen in cold atomic gases. SCES are difficult materials to model theoretically because of the highly time-dependent fluctuations of their electronic constituents. An important emerging technology is the multicore processor, where an increasingly large number of CPUs ("cores") are juxtaposed on a single chip and thus are extremely closely coupled. The resulting (expected) speedup in computational throughput comprises a promising path to sidestep the well publicized breakdown of Moore's law in semiconductor technology.This project involves the development of advanced computational physics methods, "Quantum Monte Carlo" and "Density Functional Theory," for studying SCES properties. The capabilities of these new approaches will be greatly enhanced by the formulation of efficient strategies for their implementation on emerging multicore processors. This work crosses the intellectual boundary between condensed matter and atomic physics, and also between physics, applied mathematics, and computer science. The applications will explore effects of interactions on novel quantum states of matter which arise from magnetic, metal-insulator, and superconducting transitions. A particular project focus will be on the effect of spatial inhomogeneities ("defects") on ordered phases of quantum systems. In addition to advancing research in computational physics and materials science, this work has broader impacts to training graduate students and postdoctoral researchers in interdisciplinaryresearch tools. The Principal Investigators have also a substantial effort in involving undergraduate students and even high school students in research, which they will continue with this project.