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The Lanczos algorithm is appreciated in many situations due to its speed and economy of storage. However, the advantage that the Lanczos basis vectors need not be kept is lost when the algorithm is used to compute the action of a matrix function on a vector. Either the basis vectors need to be kept, or the Lanczos process needs to be applied twice. In this study we describe an augmented Lanczos algorithm to compute a dot product relative to a function of a large sparse symmetric matrix, without keeping the basis vectors.

An Augmented Lanczos Algorithm for the Efficient Computation of a Dot-Product of a Function of a Large Sparse Symmetric Matrix