Multi-Pass Streaming Lower Bounds for Approximating Max-Cut
Yumou Fei, Dor Minzer, Shuo Wang
Abstract
In the Max-Cut problem in the streaming model, an algorithm is given the edges of an unknown graph in some fixed order, and its goal is to approximate the size of the largest cut in G. Improving upon an earlier result of Kapralov, Khanna and Sudan, it was shown by Kapralov and Krachun that for all , no memory streaming algorithm can achieve a -approximation for Max-Cut. Their result holds for single-pass streams, i.e. the setting in which the algorithm only views the stream once, and it was open whether multi-pass access may help. The state-of-the-art result along these lines, due to Assadi and N, rules out arbitrarily good approximation algorithms with constantly many passes and space for any . We improve upon this state-of-the-art result, showing that any non-trivial approximation algorithm for Max-Cut requires either polynomially many passes or polynomially large space. More specifically, we show that for all , a k-pass streaming -approximation algorithm for Max-Cut requires space. This result leads to a similar lower bound for the Maximum Directed Cut problem, showing the near optimality of the algorithm of [Saxena, Singer, Sudan, Velusamy, SODA 2025]. Our lower bounds proceed by showing a communication complexity lower bound for the Distributional Implicit Hidden Partition (DIHP) Problem, introduced by Kapralov and Krachun. While a naive application of the discrepancy method fails, we identify a property of protocols called “globalness”, and show that (1) any protocol for DIHP can be turned into a global protocol, (2) the discrepancy of a global protocol must be small. The second step is the more technically involved step in the argument, and therein we use global hypercontractive inequalities, and more specifically strong quantitative versions of the level- d inequality for global functions.
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- Multi-Pass Graph Streaming Lower Bounds for Cycle Counting, MAX-CUT, Matching Size, and Other ProblemsSepehr Assadi, Gillat Kol, Raghuvansh R. Saxena, Huacheng YuFOCS 2020 · 19 citations
- Optimal Streaming Approximations for all Boolean Max-2CSPs and Max-ksatChi-Ning Chou, Alexander Golovnev, Santhoshini VelusamyFOCS 2020 · 18 citations
- Graph streaming lower bounds for parameter estimation and property testing via a streaming XOR lemmaSepehr Assadi, Vishvajeet NSTOC 2021 · 12 citations
- Linear space streaming lower bounds for approximating CSPsChi-Ning Chou, Alexander Golovnev, Madhu Sudan, Ameya Velingker et al.STOC 2022 · 9 citations
- Streaming complexity of CSPs with randomly ordered constraintsRaghuvansh R. Saxena, Noah Singer, Madhu Sudan, Santhoshini VelusamySODA 2023 · 7 citations
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