8,010 research outputs found

    Adaptive multiscale model reduction with Generalized Multiscale Finite Element Methods

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    In this paper, we discuss a general multiscale model reduction framework based on multiscale finite element methods. We give a brief overview of related multiscale methods. Due to page limitations, the overview focuses on a few related methods and is not intended to be comprehensive. We present a general adaptive multiscale model reduction framework, the Generalized Multiscale Finite Element Method. Besides the method's basic outline, we discuss some important ingredients needed for the method's success. We also discuss several applications. The proposed method allows performing local model reduction in the presence of high contrast and no scale separation

    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(dlogk)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+ϵ)(1+\epsilon)-approximation of the \v{C}ech filtration has to contain nΩ(loglogn)n^{\Omega(\log\log n)} features, provided that ϵ<1log1+cn\epsilon <\frac{1}{\log^{1+c} n} for c(0,1)c\in(0,1).Comment: 24 pages, 1 figur

    Introduction to Regularity Structures

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    These are short notes from a series of lectures given at the University of Rennes in June 2013, at the University of Bonn in July 2013, at the XVIIth Brazilian School of Probability in Mambucaba in August 2013, and at ETH Zurich in September 2013. We give a concise overview of the theory of regularity structures as exposed in Hairer (2014). In order to allow to focus on the conceptual aspects of the theory, many proofs are omitted and statements are simplified. We focus on applying the theory to the problem of giving a solution theory to the stochastic quantisation equations for the Euclidean Φ34\Phi^4_3 quantum field theory.Comment: 33 page
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