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Testing graphs against an unknown distribution

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Abstract

The area of graph property testing seeks to understand the relation between the global properties of a graph and its local statistics. In the classical model, the local statistics of a graph is defined relative to a uniform distribution over the graph’s vertex set. A graph property \({\cal P}\) is said to be testable if the local statistics of a graph can allow one to distinguish between graphs satisfying \({\cal P}\) and those that are far from satisfying it.

Goldreich recently introduced a generalization of this model in which one endows the vertex set of the input graph with an arbitrary and unknown distribution, and asked which of the properties that can be tested in the classical model can also be tested in this more general setting. We completely resolve this problem by giving a (surprisingly “clean ”) characterization of these properties. To this end, we prove a removal lemma for vertex weighted graphs which is of independent interest.

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Acknowledgements

We are grateful to an anonymous referee for spotting a gap in the proof of Theorem 1 in a preliminary version of the paper.

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Authors and Affiliations

  1. School of Mathematics, Tel Aviv University, Tel Aviv, 69978, Israel

    Lior Gishboliner & Asaf Shapira

Authors
  1. Lior Gishboliner
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  2. Asaf Shapira
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Corresponding author

Correspondence to Asaf Shapira.

Additional information

A preliminary version of this paper has appeared in the Proceedings of STOC’ 19.

Supported in part by ERC Starting Grant 633509.

Supported in part by ISF Grant 1028/16 and ERC Starting Grant 633509.

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Gishboliner, L., Shapira, A. Testing graphs against an unknown distribution. Isr. J. Math. 245, 787–837 (2021). https://doi.org/10.1007/s11856-021-2228-8

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  • DOI: https://doi.org/10.1007/s11856-021-2228-8

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