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Track A: Algorithms, Complexity and Games

DOI: 10.4230/LIPIcs.ICALP.2026.91

Faster Weak Expander Decompositions and Approximate Max Flow

Authors: Henry Fleischmann, George Z. Li, and Jason Li

Published in: LIPIcs, Volume 374, 53rd International Colloquium on Automata, Languages, and Programming (ICALP 2026)

Abstract

We give faster algorithms for weak expander decompositions and approximate max flow on undirected graphs. First, we show that it is possible to "warm start" the cut-matching game when computing weak expander decompositions, avoiding the cost of the recursion depth. Our algorithm is also flexible enough to support weaker flow subroutines than previous algorithms. Our second contribution is to streamline the recent non-recursive approximate max flow algorithm of Li, Rao, and Wang (SODA, 2025) and adapt their framework to use our new weak expander decomposition primitive. Consequently, we give an approximate max flow algorithm within a few logarithmic factors of the limit of expander decomposition-based approaches.

Cite as

Henry Fleischmann, George Z. Li, and Jason Li. Faster Weak Expander Decompositions and Approximate Max Flow. In 53rd International Colloquium on Automata, Languages, and Programming (ICALP 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 374, pp. 91:1-91:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{fleischmann_et_al:LIPIcs.ICALP.2026.91,
  author =	{Fleischmann, Henry and Li, George Z. and Li, Jason},
  title =	{{Faster Weak Expander Decompositions and Approximate Max Flow}},
  booktitle =	{53rd International Colloquium on Automata, Languages, and Programming (ICALP 2026)},
  pages =	{91:1--91:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-428-4},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{374},
  editor =	{Bhattacharya, Sayan and Nanongkai, Danupon and Benedikt, Michael and Puppis, Gabriele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2026.91},
  URN =		{urn:nbn:de:0030-drops-264800},
  doi =		{10.4230/LIPIcs.ICALP.2026.91},
  annote =	{Keywords: max flow, expander decompositions, congestion approximators, cut-matching game}
}

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DOI: 10.4230/LIPIcs.ITCS.2024.19

Spanning Adjacency Oracles in Sublinear Time

Authors: Greg Bodwin and Henry Fleischmann

Published in: LIPIcs, Volume 287, 15th Innovations in Theoretical Computer Science Conference (ITCS 2024)

Abstract

Suppose we are given an n-node, m-edge input graph G, and the goal is to compute a spanning subgraph H on O(n) edges. This can be achieved in linear O(m + n) time via breadth-first search. But can we hope for sublinear runtime in some range of parameters - for example, perhaps O(n^{1.9}) worst-case runtime, even when the input graph has n² edges? If the goal is to return H as an adjacency list, there are simple lower bounds showing that Ω(m + n) runtime is necessary. If the goal is to return H as an adjacency matrix, then we need Ω(n²) time just to write down the entries of the output matrix. However, we show that neither of these lower bounds still apply if instead the goal is to return H as an implicit adjacency matrix, which we call an adjacency oracle. An adjacency oracle is a data structure that gives a user the illusion that an adjacency matrix has been computed: it accepts edge queries (u, v), and it returns in near-constant time a bit indicating whether or not (u, v) ∈ E(H). Our main result is that, for any 0 < ε < 1, one can construct an adjacency oracle for a spanning subgraph on at most (1+ε)n edges, in Õ(n ε^{-1}) time (hence sublinear time on input graphs with m ≫ n edges), and that this construction time is near-optimal. Additional results include constructions of adjacency oracles for k-connectivity certificates and spanners, which are similarly sublinear on dense-enough input graphs. Our adjacency oracles are closely related to Local Computation Algorithms (LCAs) for graph sparsifiers; they can be viewed as LCAs with some computation moved to a preprocessing step, in order to speed up queries. Our oracles imply the first LCAs for computing sparse spanning subgraphs of general input graphs in Õ(n) query time, which works by constructing our adjacency oracle, querying it once, and then throwing the rest of the oracle away. This addresses an open problem of Rubinfeld [CSR '17].

Cite as

Greg Bodwin and Henry Fleischmann. Spanning Adjacency Oracles in Sublinear Time. In 15th Innovations in Theoretical Computer Science Conference (ITCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 287, pp. 19:1-19:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{bodwin_et_al:LIPIcs.ITCS.2024.19,
  author =	{Bodwin, Greg and Fleischmann, Henry},
  title =	{{Spanning Adjacency Oracles in Sublinear Time}},
  booktitle =	{15th Innovations in Theoretical Computer Science Conference (ITCS 2024)},
  pages =	{19:1--19:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-309-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{287},
  editor =	{Guruswami, Venkatesan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2024.19},
  URN =		{urn:nbn:de:0030-drops-195475},
  doi =		{10.4230/LIPIcs.ITCS.2024.19},
  annote =	{Keywords: Graph algorithms, Sublinear algorithms, Data structures, Graph theory}
}

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Documents authored by Fleischmann, Henry

Faster Weak Expander Decompositions and Approximate Max Flow

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Spanning Adjacency Oracles in Sublinear Time

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