The Hardness of Approximating the Threshold Dimension, Boxicity and Cubicity of a Graph
Abhijin Adiga, Diptendu Bhowmick, L. Sunil Chandran

TL;DR
This paper proves that approximating the threshold dimension, boxicity, and cubicity of a graph within certain factors is computationally hard, even for structured split graphs, and shows NP-completeness for specific cases.
Contribution
It establishes strong hardness of approximation results for threshold dimension, boxicity, and cubicity, and proves NP-completeness for boxicity at most 3 in split graphs.
Findings
No polynomial-time approximation within factor O(n^{0.5-ε}) for threshold dimension, boxicity, and cubicity unless NP=ZPP.
Hardness results hold even for split graphs, a highly structured class.
NP-complete to decide if a split graph has boxicity ≤ 3.
Abstract
A -dimensional box is the Cartesian product where each is a closed interval on the real line. The {\it boxicity} of a graph , denoted as , is the minimum integer such that can be represented as the intersection graph of a collection of -dimensional boxes. A unit cube in -dimensional space or a -cube is defined as the Cartesian product where each is a closed interval on the real line of the form . The {\it cubicity} of , denoted as , is the minimum integer such that can be represented as the intersection graph of a collection of -cubes. The {\it threshold dimension} of a graph is the smallest integer such that can be covered by threshold spanning subgraphs of . In this paper we will show that there exists…
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Taxonomy
TopicsAdvanced Graph Theory Research · Graph Theory and Algorithms · Graph Labeling and Dimension Problems
