David Farrelly of Utah State University is supported by the Chemical Theory, Models and Computational Methods program in the Chemistry Division to develop a new theoretical and computational approach to the quantum Diffusion Monte Carlo (DMC) method. Application will be made to molecular and cluster dynamics. In the proposed algorithm, the nodal hypersurfaces of wave functions - a key input to DMC calculations - are computed and improved on-the-fly throughout the calculation. The nodal search is formulated as a multi-dimensional optimization problem, and is solved using genetic algorithms. Both methodological and algorithmic developments are underway and these will allow efficient utilization of current and future high-end parallel computers. Simulations of problems of current interest are being performed: these include the spectroscopy and dynamics of molecules and molecular clusters doped into small bosonic droplets of helium-4 atoms or para-hydrogen molecules. Bosonic solvent droplets have been used experimentally as nanocryostats to form exotic species and aggregates, as chemical nanoreactors to isolate otherwise unstable reaction intermediates, and as spectroscopic matrices to study large organic molecules and nanostructures.
Farrelly and his coworkers are developing a new theoretical and computational approach to Quantum Monte Carlo algorithms used for investigating the quantum dynamics of complex molecular systems, including clusters of atoms. Usually one of the inputs to these algorithms is the nodal structure of the quantum wavefunctions, i.e., the places where the wavefunction is zero. Unfortunately, this structure is not usually known prior to the calculation so it must be "guessed at". In this project, the nodal structure is computed "on the fly" during the calculation using state-of-the art optimization methods, leading to a more accurate calculation. Quantum Monte Carlo methods are widely used in fields such as the rational design of advanced new materials, simulations of processes important in atmospheric chemistry (e.g., aerosol formation), and cold-atom physics (e.g., quantum computing and developing essentially noise-free atomic analogs of electronics using cold atoms). Undergraduate and graduate students, including those from underrepresented groups, are being trained in state-of-the art computational methods. The resulting computer program is being designed so as to be useful and broadly accessible to other researchers.
