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Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients

机译:一类具有随机系数的PDES的拟最优随机Galerkin方法的收敛性

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In this work we consider quasi-optimal versions of the Stochastic Galerkin method for solving linear elliptic PDEs with stochastic coefficients. In particular, we consider the case of a finite number N of random inputs and an analytic dependence of the solution of the PDE with respect to the parameters in a polydisc of the complex plane C~N. We show that a quasi-optimal approximation is given by a Galerkin projection on a weighted (anisotropic) total degree space and prove a (sub)exponential convergence rate. As a specific application we consider a thermal conduction problem with non-overlapping inclusions of random conductivity. Numerical results show the sharpness of our estimates.
机译:在这项工作中,我们考虑了随机Galerkin方法的拟最佳形式,用于求解具有随机系数的线性椭圆PDE。特别地,我们考虑有限数量的N个随机输入的情况,以及PDE的解对复平面C_N的多碟中的参数的解析依赖性。我们表明,在加权(各向异性)总度空间上的Galerkin投影给出了拟最佳逼近,并证明了(次)指数收敛速度。作为一个特定的应用,我们考虑一个导热问题,其中包含随机导热率的非重叠夹杂物。数值结果表明了我们估计的准确性。

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