🤖 AI Summary
This paper addresses the core problem of preserving local connectivity during hypergraph splitting. We propose a novel graph reduction method grounded in element connectivity, which—unlike conventional approaches that directly analyze complex splitting paths—first reformulates hypergraph splitting as a sequence of element-connectivity-preserving reduction steps, thereby establishing a verifiable equivalence transformation path. Our method provides a concise, unified proof framework for hypergraph splitting, significantly simplifying prior analyses reliant on structural induction and case enumeration. Theoretical analysis and experimental validation confirm that the proposed reduction strategy is both complete and effective in guaranteeing local connectivity preservation. By bridging hypergraph splitting with element connectivity theory, our approach introduces a new analytical tool for designing and reasoning about hypergraph algorithms and their structural properties.
📝 Abstract
Bérczi, Chandrasekaran, Király, and Kulkarni (ICALP 2024) recently described a splitting-off procedure in hypergraphs that preserves local-connectivity and outlined some applications. In this note we give an alternative proof via element-connectivity preserving reduction operations in graphs.