Improving Global Optimisation Search Schemes for Quantum Chemical Simulations

Michael Groves, California State University-Fullerton

Usage Details

The intern will develop protocols which will enhance the success rate and speed of the genetic algorithm, a global optimisation search scheme. The student will use existing data to create protocols in Python to intelligently create a starting set of geometries to more broadly sample configuration space then can be created by pure randomization. They will use quantum mechanics based calculations to relax trial structures and use machine learning algorithms to cluster during global optimisation search runs to test the effectiveness of their protocols. New strategies will then be tested on new trial systems to determine their capabilities on a broader set of systems. To test the effectiveness of global optimisation search schemes, hundreds of runs comprised of thousands of trial structures must be calculated to get the statistics necessary to quantify improvements with statistical accuracy to benchmark improvements.