Tight Double Exponential Lower Bounds

Ivan Bliznets*, Markus Hecher

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

3 Citations (Scopus)
55 Downloads (Pure)

Abstract

The majority of established algorithms have polynomial, exponential, or factorial runtime complexities. Examples of problems that admit tight double or even triple exponential bounds on computational complexity are relatively rare. The Choosability problem is one such example. For this problem, Marx and Mitsou [ICALP 2016] presented a quite sophisticated proof that shows there is no O(22o(tw))nO(1) time algorithm parameterized by treewidth tw, assuming ETH. In our paper, we show how we almost immediately come to the same conclusion knowing the reduction from ∀∃-TQBF to the Choosability problem. Besides, in some sense, we provide a factory that produces problems with tight double exponential lower bounds not only in terms of treewidth but also pathwidth, cutwidth, and bandwidth. It was suspected that the Π2P-complete or Σ2P-complete problems require a double exponential time algorithm in terms of treewidth. However, in our paper, we provide a counterexample to this statement.

Original languageEnglish
Title of host publicationTheory and Applications of Models of Computation - 18th Annual Conference, TAMC 2024, Proceedings
EditorsXujin Chen, Bo Li
PublisherSpringer
Pages124-136
Number of pages13
ISBN (Electronic)978-981-97-2340-9
ISBN (Print)978-981-97-2339-3
DOIs
Publication statusPublished - 3-May-2024
Event18th Annual Conference on Theory and Applications of Models of Computation, TAMC 2024 - Hong Kong, China
Duration: 13-May-202415-May-2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14637 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th Annual Conference on Theory and Applications of Models of Computation, TAMC 2024
Country/TerritoryChina
CityHong Kong
Period13/05/202415/05/2024

Keywords

  • Choosability
  • double exponential
  • lower bounds

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