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    Lower Bounds for Approximating Graph Parameters via Communication Complexity

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    In a celebrated work, Blais, Brody, and Matulef [Blais et al., 2012] developed a technique for proving property testing lower bounds via reductions from communication complexity. Their work focused on testing properties of functions, and yielded new lower bounds as well as simplified analyses of known lower bounds. Here, we take a further step in generalizing the methodology of [Blais et al., 2012] to analyze the query complexity of graph parameter estimation problems. In particular, our technique decouples the lower bound arguments from the representation of the graph, allowing it to work with any query type. We illustrate our technique by providing new simpler proofs of previously known tight lower bounds for the query complexity of several graph problems: estimating the number of edges in a graph, sampling edges from an almost-uniform distribution, estimating the number of triangles (and more generally, r-cliques) in a graph, and estimating the moments of the degree distribution of a graph. We also prove new lower bounds for estimating the edge connectivity of a graph and estimating the number of instances of any fixed subgraph in a graph. We show that the lower bounds for estimating the number of triangles and edge connectivity also hold in a strictly stronger computational model that allows access to uniformly random edge samples

    On The Multiparty Communication Complexity of Testing Triangle-Freeness

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    In this paper we initiate the study of property testing in simultaneous and non-simultaneous multi-party communication complexity, focusing on testing triangle-freeness in graphs. We consider the coordinator\textit{coordinator} model, where we have kk players receiving private inputs, and a coordinator who receives no input; the coordinator can communicate with all the players, but the players cannot communicate with each other. In this model, we ask: if an input graph is divided between the players, with each player receiving some of the edges, how many bits do the players and the coordinator need to exchange to determine if the graph is triangle-free, or far\textit{far} from triangle-free? For general communication protocols, we show that O~(k(nd)1/4+k2)\tilde{O}(k(nd)^{1/4}+k^2) bits are sufficient to test triangle-freeness in graphs of size nn with average degree dd (the degree need not be known in advance). For simultaneous\textit{simultaneous} protocols, where there is only one communication round, we give a protocol that uses O~(kn)\tilde{O}(k \sqrt{n}) bits when d=O(n)d = O(\sqrt{n}) and O~(k(nd)1/3)\tilde{O}(k (nd)^{1/3}) when d=Ω(n)d = \Omega(\sqrt{n}); here, again, the average degree dd does not need to be known in advance. We show that for average degree d=O(1)d = O(1), our simultaneous protocol is asymptotically optimal up to logarithmic factors. For higher degrees, we are not able to give lower bounds on testing triangle-freeness, but we give evidence that the problem is hard by showing that finding an edge that participates in a triangle is hard, even when promised that at least a constant fraction of the edges must be removed in order to make the graph triangle-free.Comment: To Appear in PODC 201
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