Infinite-Dimensional Quadrature and Quantization

We study numerical integration of Lipschitz functionals on a Banach space by means of deterministic and randomized (Monte Carlo) algorithms. This quadrature problem is shown to be closely related to the problem of quantization of the underlying probability measure. In addition to the general setting we analyze in particular integration w.r.t. Gaussian measures and distributions of diffusion processes. We derive lower bounds for the worst case error of every algorithm in terms of its computational cost, and we present matching upper bounds, up to logarithms, and corresponding almost optimal algorithms. As auxiliary results we determine the asymptotic behaviour of quantization numbers and Kolmogorov widths for diffusion processes.