eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Leibniz International Proceedings in Informatics
1868-8969
2023-08-30
18:1
18:18
10.4230/LIPIcs.ESA.2023.18
article
Space-Efficient Parameterized Algorithms on Graphs of Low Shrubdepth
Bergougnoux, Benjamin
1
Chekan, Vera
2
https://orcid.org/0000-0002-6165-1566
Ganian, Robert
3
https://orcid.org/0000-0002-7762-8045
Kanté, Mamadou Moustapha
4
https://orcid.org/0000-0003-1838-7744
Mnich, Matthias
5
https://orcid.org/0000-0002-4721-5354
Oum, Sang-il
6
7
https://orcid.org/0000-0002-6889-7286
Pilipczuk, Michał
1
van Leeuwen, Erik Jan
8
https://orcid.org/0000-0001-5240-7257
Institute of Informatics, University of Warsaw, Poland
Humboldt-Universität zu Berlin, Germany
Algorithms and Complexity Group, TU Wien, Austria
Université Clermont Auvergne, Clermont Auvergne INP, LIMOS, CNRS, Clermont-Ferrand, France
Hamburg University of Technology, Institute for Algorithms and Complexity, Germany
Discrete Mathematics Group, Institute for Basic Science (IBS), Daejeon, Korea
Department of Mathematical Sciences, KAIST, Daejeon, Korea
Dept. Information and Computing Sciences, Utrecht University, The Netherlands
Dynamic programming on various graph decompositions is one of the most fundamental techniques used in parameterized complexity. Unfortunately, even if we consider concepts as simple as path or tree decompositions, such dynamic programming uses space that is exponential in the decomposition’s width, and there are good reasons to believe that this is necessary. However, it has been shown that in graphs of low treedepth it is possible to design algorithms which achieve polynomial space complexity without requiring worse time complexity than their counterparts working on tree decompositions of bounded width. Here, treedepth is a graph parameter that, intuitively speaking, takes into account both the depth and the width of a tree decomposition of the graph, rather than the width alone.
Motivated by the above, we consider graphs that admit clique expressions with bounded depth and label count, or equivalently, graphs of low shrubdepth. Here, shrubdepth is a bounded-depth analogue of cliquewidth, in the same way as treedepth is a bounded-depth analogue of treewidth. We show that also in this setting, bounding the depth of the decomposition is a deciding factor for improving the space complexity. More precisely, we prove that on n-vertex graphs equipped with a tree-model (a decomposition notion underlying shrubdepth) of depth d and using k labels,
- Independent Set can be solved in time 2^𝒪(dk) ⋅ n^𝒪(1) using 𝒪(dk²log n) space;
- Max Cut can be solved in time n^𝒪(dk) using 𝒪(dk log n) space; and
- Dominating Set can be solved in time 2^𝒪(dk) ⋅ n^𝒪(1) using n^𝒪(1) space via a randomized algorithm. We also establish a lower bound, conditional on a certain assumption about the complexity of Longest Common Subsequence, which shows that at least in the case of Independent Set the exponent of the parametric factor in the time complexity has to grow with d if one wishes to keep the space complexity polynomial.
https://drops.dagstuhl.de/storage/00lipics/lipics-vol274-esa2023/LIPIcs.ESA.2023.18/LIPIcs.ESA.2023.18.pdf
Parameterized complexity
shrubdepth
space complexity
algebraic methods