Approximating Sparsest Cut in Low-Treewidth Graphs via Combinatorial Diameter
Parinya Chalermsook, Matthias Kaul, Matthias Mnich, Joachim Spoerhase,, Sumedha Uniyal, Daniel Vaz

TL;DR
This paper advances algorithms for the sparsest cut problem in low-treewidth graphs, achieving better approximation factors with nearly optimal runtime by introducing a new measure called combinatorial diameter.
Contribution
It presents new approximation algorithms with improved runtime and approximation ratios for the sparsest cut problem in graphs of bounded treewidth, utilizing the novel combinatorial diameter measure.
Findings
Achieves a factor-$O(k^2)$ approximation in $2^{O(k)} ext{poly}(n)$ time.
Provides a $O(1/ ext{epsilon}^2)$ approximation with nearly single-exponential runtime in $k$.
Introduces the combinatorial diameter measure for tree decompositions, which may be of independent interest.
Abstract
The fundamental sparsest cut problem takes as input a graph together with the edge costs and demands, and seeks a cut that minimizes the ratio between the costs and demands across the cuts. For -node graphs~ of treewidth~, \chlamtac, Krauthgamer, and Raghavendra (APPROX 2010) presented an algorithm that yields a factor- approximation in time . Later, Gupta, Talwar and Witmer (STOC 2013) showed how to obtain a -approximation algorithm with a blown-up run time of . An intriguing open question is whether one can simultaneously achieve the best out of the aforementioned results, that is, a factor- approximation in time . In this paper, we make significant progress towards this goal, via the following results: (i) A factor- approximation that runs in time $2^{O(k)}…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Advanced Graph Theory Research · Optimization and Search Problems
