The continuum quantum Monte Carlo (QMC) method offers a unique path towards high accuracy calculations for a broad range of electronic systems from molecules to solids. Localization, van der Waals interactions, and strong correlations between electrons can all be treated with high fidelity. Unlike other electronic structure methods, QMC explicitly uses correlated wave functions to describe the many-body effects in an efficient and compact manner. An exact mapping between the Schrodinger equation and an equivalent stochastic process is used both to represent and obtain the actual solution by stochastic methods. Electrons and ions are represented in the continuum, rather than on a lattice, allowing, in principle, QMC to address a much broader range of materials phenomena. The stochastic representation allows the compute intensive parts of the algorithms to be parallelized along several domains (random walkers domain, basis and orbital domain, k-point domain, etc.) independently and efficiently making it an ideal method for High Performance Computing.
Recent theoretical and algorithmic development and ever-growing computing powers have increased the productivity of QMC by many orders of magnitude and opened up realistic opportunities to compute and predict materials properties. This presentation will describe the QMC theory implemented in the QMCPACK code, the computational schemes employed and planned to speed up the code for the next generation of supercomputers, and some highlights of the applications on material science and quantum chemistry.
Bio:
Dr. Anouar Benali is an Assistant Computational Scientist within the Argonne Leadership Computing Facility. He obtained a B.Sc. and a M.Sc in Physics from the University of Sciences and Technology of Lille (France) in 2007, and a Ph.D. in Theoretical Physical Chemistry from the University of Toulouse (France) in 2010. He was post-doctoral fellow at Argonne National Laboratory (2011-2013) prior to transitioning to his actual position.
His primary research interest is Quantum Monte Carlo (QMC) methods for materials and molecular systems. Dr. Benali is a developer of the QMCPACK simulation package and his work focuses on implementing and speeding QMC algorithms for the current and future generation of High Performance Computers (HPC). His domain of expertise covers a large field of applications using QMC, from catalysis to drug design. His work during his postdoctoral fellowship was the first to demonstrate the accuracy of QMC on large bio-molecules and helped set the method as a benchmark method. Since, he has been focusing on battery design, biological systems, catalysis and Transition Metal oxides and their applications in semiconductors.