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An Optimal Algorithm for Triangle Counting in the Stream

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arxiv 2105.01785 v2 pith:GM22EGV2 submitted 2021-05-04 cs.DS

classification cs.DS
keywords deltanumberalgorithmleftrighttrianglesfracbound
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

We present a new algorithm for approximating the number of triangles in a graph $G$ whose edges arrive as an arbitrary order stream. If $m$ is the number of edges in $G$, $T$ the number of triangles, $\Delta_E$ the maximum number of triangles which share a single edge, and $\Delta_V$ the maximum number of triangles which share a single vertex, then our algorithm requires space: \[ \widetilde{O}\left(\frac{m}{T}\cdot \left(\Delta_E + \sqrt{\Delta_V}\right)\right) \] Taken with the $\Omega\left(\frac{m \Delta_E}{T}\right)$ lower bound of Braverman, Ostrovsky, and Vilenchik (ICALP 2013), and the $\Omega\left( \frac{m \sqrt{\Delta_V}}{T}\right)$ lower bound of Kallaugher and Price (SODA 2017), our algorithm is optimal up to log factors, resolving the complexity of a classic problem in graph streaming.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Quantum Communication Lower Bounds for Search Problems via Matrix Discrepancy

    quant-ph 2026-07 accept novelty 7.5 of 10

    A matrix-discrepancy argument proves tight one-way quantum lower bounds for collision finding (Ω(N^{1/4})) and for streaming triangle finding (Ω(√Δ_V)) where Boolean-Hidden-Matching reductions fail.

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