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Complexity of Computing the Anti-Ramsey Numbers for Paths

Complexity of computing the anti-Ramsey numbers for paths
Authors: Saeed Akhoondian Amiri; Alexandru Popa 0001; Mohammad Roghani; Golnoosh Shahkarami; Reza Soltani; Hossein Vahidi 0001;

Complexity of Computing the Anti-Ramsey Numbers for Paths

Abstract

The anti-Ramsey numbers are a fundamental notion in graph theory, introduced in 1978, by Erd\" os, Simonovits and S\' os. For given graphs $G$ and $H$ the \emph{anti-Ramsey number} $\textrm{ar}(G,H)$ is defined to be the maximum number $k$ such that there exists an assignment of $k$ colors to the edges of $G$ in which every copy of $H$ in $G$ has at least two edges with the same color. There are works on the computational complexity of the problem when $H$ is a star. Along this line of research, we study the complexity of computing the anti-Ramsey number $\textrm{ar}(G,P_k)$, where $P_k$ is a path of length $k$. First, we observe that when $k = Ω(n)$, the problem is hard; hence, the challenging part is the computational complexity of the problem when $k$ is a fixed constant. We provide a characterization of the problem for paths of constant length. Our first main contribution is to prove that computing $\textrm{ar}(G,P_k)$ for every integer $k>2$ is NP-hard. We obtain this by providing several structural properties of such coloring in graphs. We investigate further and show that approximating $\textrm{ar}(G,P_3)$ to a factor of $n^{-1/2 - ε}$ is hard already in $3$-partite graphs, unless P=NP. We also study the exact complexity of the precolored version and show that there is no subexponential algorithm for the problem unless ETH fails for any fixed constant $k$. Given the hardness of approximation and parametrization of the problem, it is natural to study the problem on restricted graph families. We introduce the notion of color connected coloring and employing this structural property. We obtain a linear time algorithm to compute $\textrm{ar}(G,P_k)$, for every integer $k$, when the host graph, $G$, is a tree.

Country
Germany
Keywords

FOS: Computer and information sciences, hardness of approximation, Analysis of algorithms and problem complexity, Anti-Ramsey, G.2.1, G.2.2, NP-hard, Computational Complexity (cs.CC), Coloring of graphs and hypergraphs, Graph algorithms (graph-theoretic aspects), Computer Science - Data Structures and Algorithms, NP-hardness, graph coloring, Coloring, Data Structures and Algorithms (cs.DS), Approximation, Generalized Ramsey theory, exact algorithm, F.2.2; G.2.1; G.2.2, 004, Algorithm, Computer Science - Computational Complexity, ETH, Graph theory (including graph drawing) in computer science, Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.), F.2.2, ddc: ddc:004

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selected citations
These citations are derived from selected sources.
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!
0
Average
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