Flips and Merge-Width in Sparse Graphs
Karolina Drabik, Ma\"el Dumas, Nikolas M\"ahlmann, Wojciech Przybyszewski, Szymon Toru\'nczyk

TL;DR
This paper demonstrates that in $K_{t,t}$-free graphs, short flip sequences can be simulated by vertex deletions, linking dense and sparse graph tameness notions, and introduces the new parameter separation-width.
Contribution
It establishes a uniform explanation for the equivalence of various tameness notions in $K_{t,t}$-free graphs and introduces the separation-width parameter.
Findings
Short flip sequences are simulatable by vertex deletions in $K_{t,t}$-free graphs.
Bounded merge-width classes have bounded expansion, with explicit construction methods.
Introduces separation-width, a new graph parameter related to merge-width and coloring numbers.
Abstract
A flip of a graph is obtained by complementing the edge relation within a set of vertices. Flips are typically used to separate vertices in a graph, by increasing the distances between them. We show that in -free graphs, every short sequence of flips can be simulated by a short sequence of vertex deletions that achieves a similar degree of separation: distances in the resulting graph are, up to a factor of three, at least as large as those obtained after the flips. This result provides a simple and uniform explanation of an emerging pattern in structural graph theory and finite model theory: the -free fragment of a tameness notion for dense graphs often coincides with a tameness notion for sparse graphs. As immediate applications, we recover the following known equivalences. In the -free setting, the dense notions (1) bounded shrub-depth, (2) bounded…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Graph Theory Research · Limits and Structures in Graph Theory · Complexity and Algorithms in Graphs
