## Convergence rates for sparse chaos approximations of elliptic problems with stochastic coefficients.(English)Zbl 1120.65004

Authors’ summary: A scalar, elliptic boundary-value problem in divergence form with stochastic diffusion coefficient $$a(x,\omega)$$ in a bounded domain $$D\subset\mathbb R^d$$ is reformulated as a deterministic, infinite-dimensional, parametric problem by separation of deterministic $$(x\in D)$$ and stochastic $$(\omega\in\Omega)$$ variables in $$a(x,\omega)$$ via Karhúnen-Loève or Legendre expansions of the diffusion coefficient. Deterministic, approximate solvers are obtained by projection of this problem into a product probability space of finite dimension $$M$$ and sparse discretizations of the resulting $$M$$-dimensional parametric problem.
Both Galerkin and collocation approximations are considered. Under regularity assumptions on the fluctuation of $$a(x,\omega)$$ in the deterministic variable $$x$$, the convergence rate of the deterministic solution algorithm is analysed in terms of the number $$N$$ of deterministic problems to be solved as both the chaos dimension $$M$$ and the multiresolution level of the sparse discretization, resp., the polynomial degree of the chaos expansion increase simultaneously.

### MSC:

 65C30 Numerical solutions to stochastic differential and integral equations 60H15 Stochastic partial differential equations (aspects of stochastic analysis) 35R60 PDEs with randomness, stochastic partial differential equations 60H35 Computational methods for stochastic equations (aspects of stochastic analysis) 65N30 Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs 65N35 Spectral, collocation and related methods for boundary value problems involving PDEs
Full Text: