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A Unified Approach to Structural Limits and Limits of Graphs with Bounded Tree-Depth

About this Title

Jaroslav Nešetřil, Jaroslav Nešetřil, Computer Science Institute of Charles University (IUUK and ITI), Malostranské nám.25, 11800 Praha 1, Czech Republic and Patrice Ossona de Mendez, Patrice Ossona de Mendez, Centre d’Analyse et de Mathématiques Sociales (CNRS, UMR 8557), 190-198 avenue de France, 75013 Paris, France

Publication: Memoirs of the American Mathematical Society
Publication Year: 2020; Volume 263, Number 1272
ISBNs: 978-1-4704-4065-7 (print); 978-1-4704-5652-8 (online)
DOI: https://doi.org/10.1090/memo/1272
Published electronically: February 26, 2020
Keywords: Graph and relational structure, graph limits, structural limits, Radon measures, Stone space, model theory, first-order logic, measurable graph
MSC: Primary 03C13, 03C98, 05C99, 06E15; Secondary 28C05

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Table of Contents

Chapters

  • 1. Introduction
  • 2. General Theory
  • 3. Modelings for Sparse Structures
  • 4. Limits of Graphs with Bounded Tree-depth
  • 5. Concluding Remarks

Abstract

In this paper we introduce a general framework for the study of limits of relational structures and graphs in particular, which is based on a combination of model theory and (functional) analysis. We show how the various approaches to graph limits fit to this framework and that they naturally appear as “tractable cases” of a general theory. As an outcome of this, we provide extensions of known results. We believe that this puts these into a broader context. The second part of the paper is devoted to the study of sparse structures. First, we consider limits of structures with bounded diameter connected components and we prove that in this case the convergence can be “almost” studied component-wise. We also propose the structure of limit objects for convergent sequences of sparse structures. Eventually, we consider the specific case of limits of colored rooted trees with bounded height and of graphs with bounded tree-depth, motivated by their role as “elementary bricks” these graphs play in decompositions of sparse graphs, and give an explicit construction of a limit object in this case. This limit object is a graph built on a standard probability space with the property that every first-order definable set of tuples is measurable. This is an example of the general concept of modeling we introduce here. Our example is also the first “intermediate class” with explicitly defined limit structures where the inverse problem has been solved.

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