balanced graphs
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Author(s):  
PuruchothamaNayakiM Et. al.

In this article, we are using the regular graph of even number of vertices and computing the distance balanced graphs. First we take a graph for satisfying regular definition and then we compute the Mostar index of that particular graph. If the Mostar index of that particular graph is zero, then the graph is said to be a distance balanced graph. So we discuss first distance balanced graph. Suppose if we delete one edge in that particular graph, that is non-regular graph, we can verify the balanced graph is whether distance balanced graph or not. We discuss and compute the Mostar index of certain regular and non-regular graphs are balanced distance or not. Finally we see few theorems are related in this topic. So in this paper, we study some distance based topological indices for regular graphs and also cubic graphs.


2020 ◽  
Vol 19 (2) ◽  
pp. 311-324
Author(s):  
Matteo Cavaleri ◽  
Alfredo Donno

2020 ◽  
Vol 31 (04) ◽  
pp. 2050027
Author(s):  
Giovanni Ferrer ◽  
Roberto Hernández Palomares

Generalized Temperley–Lieb–Jones (TLJ) 2-categories associated to weighted bidirected graphs were introduced in unpublished work of Morrison and Walker. We introduce unitary modules for these generalized TLJ 2-categories as strong ∗-pseudofunctors into the ∗-2-category of row-finite separable bigraded Hilbert spaces. We classify these modules up to ∗-equivalence in terms of weighted bi-directed fair and balanced graphs in the spirit of Yamagami’s classification of fiber functors on TLJ categories and DeCommer and Yamashita’s classification of unitary modules for [Formula: see text].


2020 ◽  
Vol 53 (2) ◽  
pp. 3037-3042
Author(s):  
Kenta Hanada ◽  
Takayuki Wada ◽  
Izumi Masubuchi ◽  
Toru Asai ◽  
Yasumasa Fujisaki

2019 ◽  
Vol 261 ◽  
pp. 123-135
Author(s):  
A.G. da Silva ◽  
S. Dantas ◽  
D. Sasaki

2019 ◽  
Vol 25 (1) ◽  
pp. 44-61
Author(s):  
Morteza Faghani ◽  
Ehsan Pourhadi

Throughout this paper, we present a new strong property of graph so-called nicely n-distance-balanced which is notably stronger than the concept of n-distance-balanced recently given by the authors. We also initially introduce a newgraph invariant which modies Szeged index and is suitable to study n-distance-balanced graphs. Looking for the graphs extremal with respect to the modiedSzeged index it turns out the n-distance-balanced graphs with odd integer n arethe only bipartite graphs which can maximize the modied Szeged index and thisalso disproves a conjecture proposed by Khalifeh et al. [Khalifeh M.H.,Youse-Azari H., Ashra A.R., Wagner S.G.: Some new results on distance-based graphinvariants, European J. Combin. 30 (2009) 1149-1163]. Furthermore, we gathersome facts concerning with the nicely n-distance-balanced graphs generated by somewell-known graph products. To enlighten the reader some examples are provided.Moreover, a conjecture and a problem are presented within the results of this article.


2018 ◽  
Vol 50 (3) ◽  
pp. 759-782
Author(s):  
Matthew Coulson ◽  
Robert E. Gaunt ◽  
Gesine Reinert

Abstract We use the Stein‒Chen method to obtain compound Poisson approximations for the distribution of the number of subgraphs in a generalised stochastic block model which are isomorphic to some fixed graph. This model generalises the classical stochastic block model to allow for the possibility of multiple edges between vertices. We treat the case that the fixed graph is a simple graph and that it has multiple edges. The former results apply when the fixed graph is a member of the class of strictly balanced graphs and the latter results apply to a suitable generalisation of this class to graphs with multiple edges. We also consider a further generalisation of the model to pseudo-graphs, which may include self-loops as well as multiple edges, and establish a parameter regime in the multiple edge stochastic block model in which Poisson approximations are valid. The results are applied to obtain Poisson and compound Poisson approximations (in different regimes) for subgraph counts in the Poisson stochastic block model and degree corrected stochastic block model of Karrer and Newman (2011).


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