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Optimal Embedding of Graphs with Nonconcurrent Longest Paths in Archimedean Tessellations

التضمين الأمثل للرسوم البيانية مع أطول المسارات غير المتزامنة في الفسيفساء الأرشيمية
Authors: Muhammad Faisal Nadeem; Ayesha Shabbir; Muhammad Imran;

Optimal Embedding of Graphs with Nonconcurrent Longest Paths in Archimedean Tessellations

Abstract

Optimal graph embeddings represent graphs in a lower dimensional space in a way that preserves the structure and properties of the original graph. These techniques have wide applications in fields such as machine learning, data mining, and network analysis. Do we have small (if possible minimal) k -connected graphs with the property that for any j vertices there is a longest path avoiding all of them? This question of Zamfirescu (1972) was the first variant of Gallai’s question (1966): Do all longest paths in a connected graph share a common vertex? Several good examples answering Zamfirescu’s question are known. In 2001, he asked to investigate the family of geometrical lattices with respect to this property. In 2017, Chang and Yuan proved the existence of such graphs in Archimedean tiling. Here, we prove that the graphs presented by Chang and Yuan are not optimal by constructing such graphs of sufficiently smaller orders. The problem of finding nonconcurrent longest paths in Archimedean tessellations refers to finding paths in a lattice such that the paths do not overlap or intersect with each other and are as long as possible. The complexity of embedding graph is still unknown. This problem can be challenging because it requires finding paths that are both long and do not intersect, which can be difficult due to the constraints of the lattice structure.

Keywords

Artificial intelligence, Computer Networks and Communications, Graph, FOS: Mathematics, Physics, Graph Spectra and Topological Indices, QA75.5-76.95, Acoustics, Discrete mathematics, Lattice (music), Computer science, Vertex (graph theory), Networks on Chip in System-on-Chip Design, Computational Theory and Mathematics, Combinatorics, Electronic computers. Computer science, Graph Theory, Computer Science, Physical Sciences, Geometry and Topology, Mathematics, Graph Theory and Algorithms, Embedding

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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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