Improved kernels for Signed Max Cut parameterized above lower bound on (r,l)-graphs
Luerbio Faria, Sulamita Klein, Ignasi Sau, Rubens Sucupira

TL;DR
This paper develops smaller kernelization algorithms for the Signed Max Cut Above Tight Lower Bound problem on special graph classes, improving kernel sizes from cubic to quadratic and linear in certain cases, thus advancing parameterized complexity analysis.
Contribution
It introduces $O(k^2)$ vertex kernels for Signed Max Cut ATLB on $(r, ext{l})$-graphs and linear kernels for specific subclasses of split graphs, extending previous kernelization results.
Findings
Kernel with $O(k^2)$ vertices on $(r, ext{l})$-graphs.
Linear kernel on subclasses of split graphs.
Problem remains NP-hard on these subclasses.
Abstract
A graph is signed if each edge is assigned or . A signed graph is balanced if there is a bipartition of its vertex set such that an edge has sign if and only if its endpoints are in different parts. The Edwards-Erd\"os bound states that every graph with vertices and edges has a balanced subgraph with at least edges. In the Signed Max Cut Above Tight Lower Bound (Signed Max Cut ATLB) problem, given a signed graph and a parameter , the question is whether has a balanced subgraph with at least edges. This problem generalizes Max Cut Above Tight Lower Bound, for which a kernel with vertices was given by Crowston et al. [ICALP 2012, Algorithmica 2015]. Crowston et al. [TCS 2013] improved this result by providing a kernel with vertices for the more general Signed Max Cut…
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Taxonomy
TopicsAdvanced Graph Theory Research · Complexity and Algorithms in Graphs · Limits and Structures in Graph Theory
