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Faster Algorithms on Linear Delta-Matroids

Authors Tomohiro Koana , Magnus Wahlström

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LIPIcs.STACS.2025.62.pdf
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  • Mathematics of computing → Matroids and greedoids
Keywords
  • Delta-matroids
  • Randomized algorithms

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Abstract

We present new algorithms and constructions for linear delta-matroids. Delta-matroids are generalizations of matroids that also capture structures such as matchable vertex sets in graphs and path-packing problems. As with matroids, an important class of delta-matroids is given by linear delta-matroids, which generalize linear matroids and are represented via a "twist" of a skew-symmetric matrix. We observe an alternative representation, termed a contraction representation over a skew-symmetric matrix. This representation is equivalent to the more standard twist representation up to O(n^ω)-time transformations (where n is the dimension of the delta-matroid and ω < 2.372 the matrix multiplication exponent), but it is much more convenient for algorithmic tasks. For instance, the problem of finding a max-weight feasible set now reduces directly to finding a max-weight basis in a linear matroid. Supported by this representation, we provide new algorithms and constructions for linear delta-matroids. In particular, we show that the union and delta-sum of linear delta-matroids are again linear delta-matroids, and that a representation for the resulting delta-matroid can be constructed in randomized time O(n^ω) (or more precisely, in O(n^ω) field operations, over a field of size at least Ω(n⋅(1/ε)), where ε > 0 is an error parameter). Previously, it was only known that these operations define delta-matroids. We also note that every projected linear delta-matroid can be represented as an elementary projection. This implies that several optimization problems over (projected) linear delta-matroids, including the coverage, delta-coverage, and parity problems, reduce (in their decision versions) to a single O(n^ω)-time matrix rank computation. Using the methods of Harvey, previously applied by Cheung, Lao and Leung for linear matroid parity, we furthermore show how to solve the search versions in the same time. This improves on the O(n⁴)-time augmenting path algorithm of Geelen, Iwata and Murota, albeit with randomization. Finally, we consider the maximum-cardinality delta-matroid intersection problem (equivalently, the maximum-cardinality delta-matroid matching problem). Using Storjohann’s algorithms for symbolic determinants, we show that such a solution can be found in O(n^{ω+1}) time. This provides the first (randomized) polynomial-time solution for the problem, thereby solving an open question of Kakimura and Takamatsu.

Cite As Get BibTex

Tomohiro Koana and Magnus Wahlström. Faster Algorithms on Linear Delta-Matroids. In 42nd International Symposium on Theoretical Aspects of Computer Science (STACS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 327, pp. 62:1-62:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.STACS.2025.62

Author Details

Tomohiro Koana
  • Utrecht University, The Netherlands
  • Research Institute for Mathematical Sciences, Kyoto University, Japan
Magnus Wahlström
  • Royal Holloway, University of London, UK

Funding

  • Koana, Tomohiro: Supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (project CRACKNP under grant agreement No. 853234). Supported by JSPS KAKENHI Grant Number JP20H05967.

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