Deterministic Minimum Steiner Cut in Maximum Flow Time

We devise a deterministic algorithm for minimum Steiner cut which uses polylogarithmic maximum flow calls and near-linear time outside of these maximum flow calls. This improves on Li and Panigrahi's (FOCS 2020) algorithm which takes $O(m^{{1+\epsilon})$} time outside of maximum flow calls. Our algorithm thus shows that deterministic minimum Steiner cut can be solved in maximum flow time up to polylogarithmic factors, given any black-box deterministic maximum flow algorithm. Our main technical contribution is a novel deterministic graph decomposition method for terminal vertices which generalizes all existing $s$-strong partitioning methods and may have future applications.