John Straub is supported by a grant from the Theoretical and Computational Chemistry Program to continue his work on developing new algorithms for global optimization, enhanced sampling and the determination of reaction pathways. Two areas of algorithmic development will be explored. The first area involves the use of generalized statistics, as opposed to Gibbs-Boltzmann statistics, which can be used to describe highly delocalized distributions of configurations for systems that are strongly localized in the standard statistics. This technique leads to a higher likelihood of finding low energy configurations. The second area of research involves an optimization technique known as quantum mechanical annealing, in which the value of Planck's constant is greatly exaggerated causing the system to `spread out` in space and more effectively seek the lowest energy configurations by tunneling through energy barriers that would otherwise be hard to climb over. This technique employs imaginary-time path integral quantum simulations in a novel way. Applications include: 1) model protein folding; 2) optimal reaction path determination; and 3) enhanced sampling of molecular configurations for the computation of average thermodynamic properties. Computer simulations have provided a number of molecular level insights into chemical processes which occur in solution and on surfaces. The technique is very powerful, but is limited by statistical sampling problems associated with the speed of current supercomputers and the time available to perform such simulations. Straub is developing a new algorithm for performing molecular simulations which should be a major improvement in statistical sampling. If successful, this new algorithm could provide a significant decrease in the amount of computational resources required to obtain meaningful sampling statistics in molecular simulations.
