Paper detail

On the adjacency dimension of graphs

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.

preprint2015arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.