A posteriori error bounds for the empirical interpolation method

We present rigorous a posteriori error bounds for the Empirical Interpolation Method (EIM). The essential ingredients are (i) analytical upper bounds for the parametric derivatives of the function to be approximated, (ii) the EIM “Lebesgue constant,” and (iii) information concerning the EIM approximation error at a finite set of points in parameter space. The bound is computed “offline” and is valid over the entire parameter domain; it is thus readily employed in (say) the “online” reduced basis context. We present numerical results that confirm the validity of our approach.