Beck, JoakimNobile, FabioTamellini, LorenzoTempone, Raul2012-08-222012-08-222012-08-22201410.1016/j.camwa.2013.03.004https://infoscience.epfl.ch/handle/20.500.14299/84983WOS:000332751300003In 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.Uncertainty QuantificationElliptic PDEs with random dataMultivariate polynomial approximationBest M –terms polynomial approximationStochastic Galerkin methodSub-exponential convergencetext::journal::journal article::research article