Quantum computing (QC) aims at addressing computations that are currently intractable by conventional supercomputers. However, to be attractive for sustainable research and industrial investments, QC must not be limited to specific computations but also be seen as potential accelerator for general purpose simulations in high-performance scientific computing. In this talk we explain how core tasks in scientific computing can be addressed by quantum algorithms, possibly combined with classical ones. In particular we describe recent advances in algorithms for decomposing and handling matrices (generic, or coming from PDE’s) in quantum computers. We also present promising methods for the solution of linear systems of equations with improvement in terms of accuracy and cost for the solution.