Papers
Topics
Authors
Recent
AI Research Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 60 tok/s
Gemini 2.5 Pro 46 tok/s Pro
GPT-5 Medium 14 tok/s Pro
GPT-5 High 15 tok/s Pro
GPT-4o 93 tok/s Pro
Kimi K2 156 tok/s Pro
GPT OSS 120B 441 tok/s Pro
Claude Sonnet 4 37 tok/s Pro
2000 character limit reached

On the adjacency dimension of graphs (1501.04647v2)

Published 19 Jan 2015 in math.CO

Abstract: A generator of a metric space is a set $S$ of points in the space with the property that every point of the space is uniquely determined by its distances from the elements of $S$. Given a simple graph $G=(V,E)$, we define the distance function $d_{G,2}:V\times V\rightarrow \mathbb{N}\cup {0}$, as $d_{G,2}(x,y)=\min{d_G(x,y),2},$ where $d_G(x,y)$ is the length of a shortest path between $x$ and $y$ and $\mathbb{N}$ is the set of positive integers. Then $(V,d_{G,2 })$ is a metric space. We say that a set $S\subseteq V$ is a $k$-adjacency generator for $G$ if for every two vertices $x,y\in V$, there exist at least $k$ vertices $w_1,w_2,...,w_k\in S$ such that $$d_{G,2}(x,w_i)\ne d_{G,2}(y,w_i),\; \mbox{for every}\; i\in {1,...,k}.$$ A minimum cardinality $k$-adjacency generator is called a $k$-adjacency basis of $G$ and its cardinality, the $k$-adjacency dimension of $G$. In this article we study the problem of finding the $k$-adjacency dimension of a graph. We give some necessary and sufficient conditions for the existence of a $k$-adjacency basis of an arbitrary graph $G$ and we obtain general results on the $k$-adjacency dimension, including general bounds and closed formulae for some families of graphs. In particular, we obtain closed formulae for the $k$-adjacency dimension of join graphs $G+H$ in terms of the $k$-adjacency dimension of $G$ and $H$. These results concern the $k$-metric dimension, as join graphs have diameter two. As we can expect, the obtained results will become important tools for the study of the $k$-metric dimension of lexicographic product graphs and corona product graphs.

Summary

We haven't generated a summary for this paper yet.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube