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EMSL Outlook Review 2005
The William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) is a national user facility that contains state-of-the-art instrumentation and expert resources available for use by researchers from academia, industry, and the national laboratory system. The facility is supported by the U.S. Department of Energy’s (DOE) Biological and Environmental Research Program, but the research conducted within the facility benefits many funding agencies, including other branches of DOE, the National Institutes of Health, the National Science Foundation, and the Department of Defense. EMSL requires the continued funding and support of its stakeholders and clients to continue to grow its mission, build its reputation as a sought-after national user facility with cutting-edge capabilities, and attract high-profile users who will work to solve the most critical scientific challenges that affect DOE and the nation. In this vein, this document has been compiled to provide these stakeholders and clients with a review document that provides an abundance of information on EMSL’s history, current research activities, and proposed future direction
Graph Theoretic Algorithms Adaptable to Quantum Computing
Computational methods are rapidly emerging as an essential tool for understanding and solving complex engineering problems, which complement the traditional tools of experimentation and theory. When considered in a discrete computational setting, many engineering problems can be reduced to a graph coloring problem. Examples range from systems design, airline scheduling, image segmentation to pattern recognition, where energy cost functions with discrete variables are extremized. However, using discrete variables over continuous variables introduces some complications when defining differential quantities, such as gradients and Hessians involved in scientific computations within solid and fluid mechanics. Consequently, graph techniques are under-utilized in this important domain. However, we have recently witnessed great developments in quantum computing where physical devices can solve discrete optimization problems faster than most well-known classical algorithms. This warrants further investigation into the re-formulation of scientific computation problems into graph-theoretic problems, thus enabling rapid engineering simulations in a soon-to-be quantum computing world.
The computational techniques developed in this thesis allow the representation of surface scalars, such as perimeter and area, using discrete variables in a graph. Results from integral geometry, specifically Cauchy-Crofton relations, are used to estimate these scalars via submodular functions. With this framework, several quantities important to engineering applications can be represented in graph-based algorithms. These include the surface energy of cracks for fracture prediction, grain boundary energy to model microstructure evolution, and surface area estimates (of grains and fibers) for generating conformal meshes. Combinatorial optimization problems for these applications are presented first.
The last two chapters describe two new graph coloring algorithms implemented on a physical quantum computing device: the D-wave quantum annealer. The first algorithm describes a functional minimization approach to solve differential equations. The second algorithm describes a realization of the Boltzmann machine learning algorithm on a quantum annealer. The latter allows generative and discriminative learning of data, which has vast applications in many fields. Theoretical aspects and the implementation of these problems are outlined with a focus on engineering applications.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168116/1/sidsriva_1.pd
Technology 2001: The Second National Technology Transfer Conference and Exposition, volume 2
Proceedings of the workshop are presented. The mission of the conference was to transfer advanced technologies developed by the Federal government, its contractors, and other high-tech organizations to U.S. industries for their use in developing new or improved products and processes. Volume two presents papers on the following topics: materials science, robotics, test and measurement, advanced manufacturing, artificial intelligence, biotechnology, electronics, and software engineering