Deterministic Minimum Steiner Cut in Maximum Flow Time
CoRR(2023)
摘要
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+ϵ) 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.
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