We bound the smoothed running time of the FLIP algorithm for local Max-Cut as a function of α, the arboricity of the input graph. We show that, with high probability and in expectation, the following holds (where n is the number of nodes and ϕ is the smoothing parameter): 1) When α = O(log^{1-δ} n) FLIP terminates in ϕ poly(n) iterations, where δ ∈ (0,1] is an arbitrarily small constant. Previous to our results the only graph families for which FLIP was known to achieve a smoothed polynomial running time were complete graphs and graphs with logarithmic maximum degree. 2) For arbitrary values of α we get a running time of ϕ n^{O(α/(log n) + log α)}. This improves over the best known running time for general graphs of ϕ n^{O(√{log n})} for α = o(log^{1.5} n). Specifically, when α = O(log n) we get a significantly faster running time of ϕ n^{O(log log n)}.
@InProceedings{schwartzman:LIPIcs.ESA.2024.98, author = {Schwartzman, Gregory}, title = {{Local Max-Cut on Sparse Graphs}}, booktitle = {32nd Annual European Symposium on Algorithms (ESA 2024)}, pages = {98:1--98:6}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-338-6}, ISSN = {1868-8969}, year = {2024}, volume = {308}, editor = {Chan, Timothy and Fischer, Johannes and Iacono, John and Herman, Grzegorz}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2024.98}, URN = {urn:nbn:de:0030-drops-211694}, doi = {10.4230/LIPIcs.ESA.2024.98}, annote = {Keywords: Algorithms, smoothed analysis} }
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