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https://dx.doi.org/10.48550/ar...
Article . 2024
License: arXiv Non-Exclusive Distribution
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A Tight Subexponential-time Algorithm for Two-Page Book Embedding

Authors: Ganian, R; Mueller, H; Ordyniak, S; Paesani, G; Rychlicki, M;

A Tight Subexponential-time Algorithm for Two-Page Book Embedding

Abstract

A book embedding of a graph is a drawing that maps vertices onto a line and edges to simple pairwise non-crossing curves drawn into pages, which are half-planes bounded by that line. Two-page book embeddings, i.e., book embeddings into 2 pages, are of special importance as they are both NP-hard to compute and have specific applications. We obtain a 2^(O(\sqrt{n})) algorithm for computing a book embedding of an n-vertex graph on two pages -- a result which is asymptotically tight under the Exponential Time Hypothesis. As a key tool in our approach, we obtain a single-exponential fixed-parameter algorithm for the same problem when parameterized by the treewidth of the input graph. We conclude by establishing the fixed-parameter tractability of computing minimum-page book embeddings when parameterized by the feedback edge number, settling an open question arising from previous work on the problem.

An extended abstract of this paper has been accepted at ICALP 2024

Keywords

feedback edge number, Computational Geometry (cs.CG), FOS: Computer and information sciences, F.2, page number, G.2, F.2; G.2, book embedding, 004, book embedding; page number; subexponential algorithms; subhamiltonicity; feedback edge number, subexponential algorithms, Computer Science - Data Structures and Algorithms, Computer Science - Computational Geometry, Data Structures and Algorithms (cs.DS), subhamiltonicity, ddc: ddc:004

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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