Deterministic Fully Dynamic SSSP and More
Jan van den Brand, Adam Karczmarz
Abstract
We present the first non-trivial fully dynamic algorithm maintaining exact single-source distances in unweighted graphs. This resolves an open problem stated by Sankowski [COCOON 2005] and van den Brand and Nanongkai [FOCS 2019]. Previous fully dynamic single-source distances data structures were all approximate, but so far, non-trivial dynamic algorithms for the exact setting could only be ruled out for polynomially weighted graphs (Abboud and Vassilevska Williams, [FOCS 2014]). The exact unweighted case remained the main case for which neither a subquadratic dynamic algorithm nor a quadratic lower bound was known.Our dynamic algorithm works on directed graphs and is deterministic, and can report a single-source shortest paths tree in subquadratic time as well. Thus we also obtain the first deterministic fully dynamic data structure for reachability (transitive closure) with subquadratic update and query time. This answers an open problem of van den Brand, Nanongkai, and Saranurak [FOCS 2019]. Finally, using the same framework we obtain the first fully dynamic data structure maintaining all-pairs -approximate distances within non-trivial sub- worst-case update time while supporting optimal-time approximate shortest path reporting at the same time. This data structure is also deterministic and therefore implies the first known non-trivial deterministic worst-case bound for recomputing the transitive closure of a digraph.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 8e1dc35d-bbb4-4a2c-bdbd-4e4ed55e5436Cited by top-tier papers3
- A Dynamic Shortest Paths Toolbox: Low-Congestion Vertex Sparsifiers and Their ApplicationsRasmus Kyng, Simon Meierhans, Maximilian Probst GutenbergSTOC 2024 · 2 citations
- From Incremental Transitive Cover to Strongly Polynomial Maximum FlowDaniel Dadush, James B. Orlin, Aaron Sidford, László A. VéghSODA 2026
- Strongly Polynomial Parallel Work-Depth Tradeoffs for Directed SSSPAdam Karczmarz, Wojciech Nadara, Marek SokolowskiSODA 2026
Builds on23
- A Refined Laser Method and Faster Matrix MultiplicationJosh Alman, Virginia Vassilevska WilliamsSODA 2021 · 275 citations
- New Bounds for Matrix Multiplication: from Alpha to OmegaVirginia Vassilevska Williams, Yinzhan Xu, Zixuan Xu, Renfei ZhouSODA 2024 · 90 citations
- Faster Matrix Multiplication via Asymmetric HashingRan Duan, Hongxun Wu, Renfei ZhouFOCS 2023 · 54 citations
- Deterministic Decremental Reachability, SCC, and Shortest Paths via Directed Expanders and Congestion BalancingAaron Bernstein, Maximilian Probst Gutenberg, Thatchaphol SaranurakFOCS 2020 · 35 citations
- Deterministic Decremental SSSP and Approximate Min-Cost Flow in Almost-Linear TimeAaron Bernstein, Maximilian Probst Gutenberg, Thatchaphol SaranurakFOCS 2021 · 27 citations
Related papers
- Subquadratic dynamic path reporting in directed graphs against an adaptive adversaryAdam Karczmarz, Anish Mukherjee, Piotr SankowskiSTOC 2022 · 5 citations
- Fully Dynamic Shortest Path Reporting Against an Adaptive AdversaryAnastasiia Alokhina, Jan van den BrandSODA 2024
- Fast Deterministic Fully Dynamic Distance ApproximationJan van den Brand, Sebastian Forster, Yasamin NazariFOCS 2022 · 7 citations
- Deterministic Incremental APSP with Polylogarithmic Update Time and StretchSebastian Forster, Yasamin Nazari, Maximilian Probst GutenbergSTOC 2023 · 2 citations
- Fully-Dynamic All-Pairs Shortest Paths: Improved Worst-Case Time and Space BoundsMaximilian Probst Gutenberg, Christian Wulff-NilsenSODA 2020 · 19 citations
