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Performant implementation of the atomic cluster expansion

Lysogorskiy, Yury; Rinaldi, Matteo; Menon, Sarath; Van Der Oord, Van; Hammerschmidt, Thomas; Mrovec, Matous; Thompson, Aidan P.; Csanyi, Gabor; Ortner, Christoph; Drautz, Ralf

The atomic cluster expansion is a general polynomial expansion of the atomic energy in multi-atom basis functions. Here we implement the atomic cluster expansion in the performant C++ code PACE that is suitable for use in large scale atomistic simulations. We briefly review the atomic cluster expansion and give detailed expressions for energies and forces as well as efficient algorithms for their evaluation. We demonstrate that the atomic cluster expansion as implemented in PACE shifts a previously established Pareto front for machine learning interatomic potentials towards faster and more accurate calculations. Moreover, general purpose parameterizations are presented for copper and silicon and evaluated in detail. We show that the new Cu and Si potentials significantly improve on the best available potentials for highly accurate large-scale atomistic simulations.

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TYPE Other Report YEAR 2021
DOIOSTI

The DPG Method for the Convection-Reaction Problem Revisited

Demkowicz, Leszek; Roberts, Nathan V.

We study both conforming and non-conforming versions of the practical DPG method for the convection-reaction problem. We determine that the most common approach for DPG stability analysis (construction of a local Fortin operator) is infeasible for the convection-reaction problem. We then develop a line of argument based on the direct construction of a global Fortin operator; we find that employing a polynomial enrichment for the test space does not suffice for this purpose, motivating the introduction of a (two-element) subgrid mesh. The argument combines mathematical analysis with numerical experiments

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TYPE Other Report YEAR 2021
DOIOSTI

Parallel Solver Framework for Mixed-Integer PDE-Constrained Optimization

Phillips, Cynthia A.; Chatter, Michelle; Eckstein, Jonathan; Erturk, Alper; El-Kady, Ihab F.; Gerbe, Romain; Kouri, Drew P.; Loughlin, William; Reinke, Charles M.; Rokkam, Rohith; Ruzzene, Massimo; Sugino, Christopher; Swanson, Calvin; Van Bloemen Waanders, Bart

ROL-PEBBL is a C++, MPI-based parallel code for mixed-integer PDE-constrained optimization (MIPDECO). In these problems we wish to optimize (control, design, etc.) physical systems, which must obey the laws of physics, when some of the decision variables must take integer values. ROL-PEBBL combines a code to efficiently search over integer choices (PEBBL = Parallel Enumeration Branch-and-Bound Library) and a code for efficient nonlinear optimization, including PDE-constrained optimization (ROL = Rapid Optimization Library). In this report, we summarize the design of ROL-PEBBL and initial applications/results. For an artificial source-inversion problem, finding sources of pollution on a grid from sparse samples, ROL-PEBBLs solution for the nest grid gave the best optimization guarantee for any general solver that gives both a solution and a quality guarantee.

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TYPE SAND Report YEAR 2021
DOIOSTI
Results 826–850 of 9,998
Results 826–850 of 9,998
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