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Department of Energy Office of Science FY2015 Early Career Research Program Abstracts, 44 Selectees for Negotiation of Financial Award, Last Updated May 6, 2015
Ensemble Simulation Techniques and Fast Randomized Algorithms Dr. Jonathan Weare, Assistant Professor Department of Statistics University of Chicago Chicago, IL 60637 This project develops novel ensemble simulation techniques and fast randomized algorithms for DOE‐mission science problems. Applications include the determination of electronic ground states of chemical systems and efficient molecular dynamics simulation for drug design. For science problems involving the estimate of statistical averages, a conventional approach is to run multiple, non‐
communicating copies of the simulation and then to average the results. In contrast, the proposed ensemble simulation techniques intentionally introduce limited communication between the copies to achieve problem‐specific goals, such as: incorporation of information from observed data; exploration of rare events of acute physical interest; or faster relaxation of a dynamical system to equilibrium. Such low‐communication schemes are ideally suited for emerging, multi‐core and many‐core computational systems. The project also explores new directions in fast numerical linear algebra methods (as motivated by the ensemble simulation approach) and includes new low‐cost iterative eigenvector solvers for large‐
scale computational physics and data analysis applications. This research was selected for funding by the Office of Advanced Scientific Computing Research. 42