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European Journal of Combinatorics
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First order convergence of matroids

Authors: Frantisek Kardos; Daniel Král'; Anita Liebenau; Lukás Mach;

First order convergence of matroids

Abstract

The model theory based notion of the first order convergence unifies the notions of the left-convergence for dense structures and the Benjamini-Schramm convergence for sparse structures. It is known that every first order convergent sequence of graphs with bounded tree-depth can be represented by an analytic limit object called a limit modeling. We establish the matroid counterpart of this result: every first order convergent sequence of matroids with bounded branch-depth representable over a fixed finite field has a limit modeling, i.e., there exists an infinite matroid with the elements forming a probability space that has asymptotically the same first order properties. We show that neither of the bounded branch-depth assumption nor the representability assumption can be removed.

Accepted to the European Journal of Combinatorics

Keywords

FOS: Computer and information sciences, Discrete Mathematics (cs.DM), limit modeling, Mathematics - Logic, Combinatorial aspects of matroids and geometric lattices, FOS: Mathematics, Mathematics - Combinatorics, Combinatorics (math.CO), QA, Logic (math.LO), Matroids in convex geometry (realizations in the context of convex polytopes, convexity in combinatorial structures, etc.), Computer Science - Discrete Mathematics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Top 10%
Average
Green
hybrid