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In this paper, we present an efficient adaptive multigrid strategy for large-scale molecular mechanics optimization. The oneway multigrid method is used with inexact approximations, such as the quasi-atomistic (QA) approximation or the blended ghost force correction (BGFC) approximation on each coarse level, combined with adaptive mesh refinements based on the gradient-based a posteriori error estimator. For crystalline defects, like vacancies, micro-crack and dislocation, sublinear complexity is observed numerically when the adaptive BGFC method is employed. For systems with more than ten millions atoms, this strategy has a fivefold acceleration in terms of CPU time.
Ptychography is a popular imaging technique that combines diffractive imaging with scanning microscopy. The technique consists of a coherent beam that is scanned across an object in a series of overlapping positions, leading to reliable and improved
The large time and length scales and, not least, the vast number of particles involved in industrial-scale simulations inflate the computational costs of the Discrete Element Method (DEM) excessively. Coarse grain models can help to lower the computa
We present details of our implementation of the Wuppertal adaptive algebraic multigrid code DD-$alpha$AMG on SIMD architectures, with particular emphasis on the Intel Xeon Phi processor (KNC) used in QPACE 2. As a smoother, the algorithm uses a domai
Distributed optimization for solving non-convex Optimal Power Flow (OPF) problems in power systems has attracted tremendous attention in the last decade. Most studies are based on the geographical decomposition of IEEE test systems for verifying the
Recently, several universal methods have been proposed for online convex optimization, and attain minimax rates for multiple types of convex functions simultaneously. However, they need to design and optimize one surrogate loss for each type of funct