Separability Properties of Monadically Dependent Graph Classes
Édouard Bonnet, Samuel Braunfeld, Ioannis Eleftheriadis, Colin Geniet, Nikolas Mählmann, Michał Pilipczuk, Wojciech Przybyszewski, Szymon Toruńczyk
TL;DR
The paper characterizes monadically dependent graph classes as exactly the flip-separable ones, introducing a dense-graph analogue of nowhere-dense separability through a bounded set of vertex flips. It develops a robust toolbox of flip metrics, partition flips, and definable flips, and proves a metric-conversion result showing partition-based locality can be captured by definable flips, enabling local sparsification. The main technical advance is a locality-driven sparsification argument: monadic dependence implies the existence of small sparsifying families that bound radius-$r$ balls by a factor $\varepsilon$, accomplished via flip-breakability, Gaifman locality, and the sunflower lemma. Conversely, flip-separability implies monadic dependence, establishing a tight equivalence. The result provides a foundational link between logical definability and local sparsification in dense graph classes, with potential implications for FO-limits and modelling limits in dense settings.
Abstract
A graph class $\mathcal C$ is monadically dependent if one cannot interpret all graphs in colored graphs from $\mathcal C$ using a fixed first-order interpretation. We prove that monadically dependent classes can be exactly characterized by the following property, which we call flip-separability: for every $r\in \mathbb{N}$, $\varepsilon>0$, and every graph $G\in \mathcal{C}$ equipped with a weight function on vertices, one can apply a bounded (in terms of $\mathcal{C},r,\varepsilon$) number of flips (complementations of the adjacency relation on a subset of vertices) to $G$ so that in the resulting graph, every radius-$r$ ball contains at most an $\varepsilon$-fraction of the total weight. On the way to this result, we introduce a robust toolbox for working with various notions of local separations in monadically dependent classes.
