Derandomizing Karger's Contraction Algorithm for Matroids
Yu Cong, Chao Xu, Yajie Zhao
Abstract
Karger's randomized contraction algorithm finds a minimum-weight cocircuit of a matroid whenever the cogirth-density ratio is bounded. We prove that the same hypothesis yields a deterministic algorithm with the same exponent. If every contraction minor of rank at least r0 of a matroid M has cogirth-density ratio at most c, then a minimum-weight cocircuit of M is computable deterministically in mO(r0) nO(c) time when the contraction minors of bounded rank have at most m parallel classes, by an algorithm that knows neither r0 nor c. As a consequence, we give a deterministic algorithm computing the cogirth of rank-p perturbed graphic matroids in 2O(p2) nO(1) time, fixed-parameter tractable in p, settling the cogirth side of a question of Geelen and Kapadia (2018). The extensions of the contraction method carry over deterministically: enumerating all near-minimum 1-cocycles, computing a minimum-weight k-cocycle, and computing the Pareto frontier under several positive criteria.
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