Quantum Monte Carlo (QMC) methods and more specifically Projector Monte Carlo methods such as Diffusion Monte Carlo (DMC) offer a unique path towards high accuracy calculations for a broad range of electronic systems, from molecules to solids. QMC solves the many-body Schrodinger equation and therefore includes explicitly and accurately effects such as van der Waals interactions and strong electronic correlations, which are often approximated by other methods. 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 promising to reach chemical accuracy (~1KCal/mol) for most materials, making a direct link between experiment and theory.<br/>Recent theoretical and algorithmic development and ever-growing computing powers have increased the productivity of DMC by many orders of magnitude and opened up realistic opportunities to compute and predict materials properties. This presentation will describe briefly the QMC theory implemented in the QMCPACK code, the computational schemes used on the next generation of supercomputers, and some highlights of the applications on quantum chemistry.

Quantum Monte Carlo in the exascale era: From algorithms to applications

254th National Meeting (2017)

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