Merge-Width and First-Order Model Checking

We introduce merge-width, a family of graph parameters that unifies several structural graph measures, including treewidth, degeneracy, twin-width, clique-width, and generalized coloring numbers. Our parameters are based on new decompositions called construction sequences. These are sequences of ever coarser partitions of the vertex set, where each pair of parts has a specified default connection, and all vertex pairs of the graph that differ from the default are marked as resolved. The radius-r merge-width is the maximum number of parts reached from a vertex by following a path of at most r resolved edges. Graph classes of bounded merge-width -for which the radius-r merge-width parameter can be bounded by a constant, for each fixed r = 1, 2, 3, . . . -include all classes of bounded expansion or of bounded twin-width, thus unifying two central notions from the Sparsity and Twin-width frameworks. Furthermore, they are preserved under first-order transductions, which attests to their robustness. We conjecture that classes of bounded merge-width are equivalent to the previously introduced classes of bounded flip-width. As our main result, we show that the model checking problem for first-order logic is fixedparameter tractable on graph classes of bounded merge-width, assuming the input includes a witnessing construction sequence. This unites and extends two previous model checking results: the result of Dvořák, Král, and Thomas for classes of bounded expansion, and the result of Bonnet, Kim, Thomassé, and Watrigant for classes of bounded twin-width. Finally, we suggest future research directions that could impact the study of structural and algorithmic graph theory, in particular of monadically dependent graph classes, which we conjecture to coincide with classes of almost bounded merge-width. Acknowledgements. We are grateful to Jakub Gajarsk ý, Nikolas Mählmann, Rose McCarty, Jakub Nowakowski, Pierre Ohlmann, Michał Pilipczuk, and Wojciech Przybyszewski for many inspiring discussions. We also thank the anonymous reviewers for numerous useful comments. ST received funding from the European Research Council (ERC) (grant agreement №948057bobr -and №101126229buka).