Compact Cactus Representations of all Non-Trivial Min-Cuts
On-Hei Solomon Lo, Jens M. Schmidt, Mikkel Thorup

TL;DR
This paper introduces a simplified contraction-based sparsifier that efficiently preserves all non-trivial min-cuts in a graph, leading to a compact cactus representation and improved algorithms for listing min-cuts.
Contribution
It presents a new contraction-based sparsification method that eliminates poly-logarithmic factors, enabling near-linear time computation and a more compact cactus representation of min-cuts.
Findings
Achieves contraction-based sparsification with O(n/δ) vertices and O(n) edges in near-linear time.
Provides a cactus representation with O(n/δ) vertices for all non-trivial min-cuts.
Improves min-cut listing time to near-linear, surpassing previous bounds.
Abstract
Recently, Kawarabayashi and Thorup presented the first deterministic edge-connectivity recognition algorithm in near-linear time. A crucial step in their algorithm uses the existence of vertex subsets of a simple graph on vertices whose contractions leave a multigraph with vertices and edges that preserves all non-trivial min-cuts of , where is the minimum degree of and hides logarithmic factors. We present a simple argument that improves this contraction-based sparsifier by eliminating the poly-logarithmic factors, that is, we show a contraction-based sparsification that leaves vertices and edges, preserves all non-trivial min-cuts and can be computed in near-linear time , where is the number of edges of . We also obtain that every simple graph has …
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