762 research outputs found

    Polynomial-Sized Topological Approximations Using The Permutahedron

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    Classical methods to model topological properties of point clouds, such as the Vietoris-Rips complex, suffer from the combinatorial explosion of complex sizes. We propose a novel technique to approximate a multi-scale filtration of the Rips complex with improved bounds for size: precisely, for nn points in Rd\mathbb{R}^d, we obtain a O(d)O(d)-approximation with at most n2O(dlog⁥k)n2^{O(d \log k)} simplices of dimension kk or lower. In conjunction with dimension reduction techniques, our approach yields a O(polylog(n))O(\mathrm{polylog} (n))-approximation of size nO(1)n^{O(1)} for Rips filtrations on arbitrary metric spaces. This result stems from high-dimensional lattice geometry and exploits properties of the permutahedral lattice, a well-studied structure in discrete geometry. Building on the same geometric concept, we also present a lower bound result on the size of an approximate filtration: we construct a point set for which every (1+Ï”)(1+\epsilon)-approximation of the \v{C}ech filtration has to contain nΩ(log⁥log⁥n)n^{\Omega(\log\log n)} features, provided that Ï”<1log⁥1+cn\epsilon <\frac{1}{\log^{1+c} n} for c∈(0,1)c\in(0,1).Comment: 24 pages, 1 figur

    A simple and efficient model for mesoscale solidification simulation of globular grain structures

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    A simple model for the solidification of globular grains in metallic alloys is presented. Based on the Voronoi diagram of the nuclei centers, it accounts for the curvature of the grains near triple junctions. The predictions of this model are close to those of more refined approaches such as the phase field method, but with a computation cost decreased by several orders of magnitude. Therefore, this model is ideally suited for granular simulations linking the behavior of individual grains to macroscopic properties of the material

    DCMIP2016: a review of non-hydrostatic dynamical core design and intercomparison of participating models

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    Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere via numerical integration of the Navier-Stokes equations. These systems have existed in one form or another for over half of a century, with the earliest discretizations having now evolved into a complex ecosystem of algorithms and computational strategies. In essence, no two dynamical cores are alike, and their individual successes suggest that no perfect model exists. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 non-hydrostatic dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school. This review includes a choice of model grid, variable placement, vertical coordinate, prognostic equations, temporal discretization, and the diffusion, stabilization, filters, and fixers employed by each syste
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