Recent successful techniques for the efficient simulation of largescale interconnect models rely on the sparsification of the inverse of the inductance matrix L. While there are several techniques for sparsifying L−1, the stability of these approximations for general interconnect structures has not been established, i.e., the sparsified reluctance and inductance matrices are not guaranteed to be positive-definite. In this paper, we present a novel technique for reluctance sparsification for general interconnect structures that enjoys several advantages: First, the resulting sparse approximation is guaranteed to be positive definite. Second, the approximation is optimal, in a certain well-defined sense. Third, owing to its computational efficiency and numerical stability, the algorithm is applicable for very large problem sizes. Finally our approach yields a compact representation of both inductance and reluctance matrices for general cases.