The matching and linear matroid intersection problems are solvable in quasi-NC, meaning that there exist deterministic algorithms that run in polylogarithmic time and use quasi-polynomially many parallel processors. However, such a parallel algorithm is unknown for linear matroid matching, which generalizes both of these problems. In this work, we propose a quasi-NC algorithm for fractional linear matroid matching, which is a relaxation of linear matroid matching and commonly generalizes fractional matching and linear matroid intersection. Our algorithm builds upon the connection of fractional matroid matching to non-commutative Edmonds' problem recently revealed by Oki and Soma (2023). As a corollary, we also solve black-box non-commutative Edmonds' problem with rank-two skew-symmetric coefficients.
@InProceedings{gurjar_et_al:LIPIcs.ESA.2024.63, author = {Gurjar, Rohit and Oki, Taihei and Raj, Roshan}, title = {{Fractional Linear Matroid Matching Is in Quasi-NC}}, booktitle = {32nd Annual European Symposium on Algorithms (ESA 2024)}, pages = {63:1--63:14}, 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.2024.63}, URN = {urn:nbn:de:0030-drops-211344}, doi = {10.4230/LIPIcs.ESA.2024.63}, annote = {Keywords: parallel algorithms, hitting set, non-commutative rank, Brascamp-Lieb polytope, algebraic algorithms} }
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