Generalized distance spectral radius of some t-partitioned transmission regular graphs

Let [Formula: see text] be an [Formula: see text]-vertex connected graph with the distance matrix [Formula: see text] and the diagonal matrix of transmissions [Formula: see text]. The generalized distance matrix of a connected graph [Formula: see text] is [Formula: see text], where [Formula: see text], [Formula: see text]. Through this matrix one can study distance, distance Laplacian, distance signless Laplacian, and [Formula: see text]- spectra of [Formula: see text] in a unified way. A simple connected graph [Formula: see text] is called [Formula: see text]-partitioned transmission regular if the vertex set of [Formula: see text] can be partitioned as [Formula: see text] such that for any pair of indices [Formula: see text] (not necessarily distinct) in [Formula: see text] and [Formula: see text], [Formula: see text] is constant. In this paper, for the spider graph [Formula: see text] and the radar graph [Formula: see text], we find matrices of order [Formula: see text] (quotient matrices) corresponding to [Formula: see text] and [Formula: see text] such that the largest eigenvalues of these matrices are generalized distance spectral radius of [Formula: see text] and [Formula: see text], respectively. Moreover, we determine the full [Formula: see text]-spectrum of [Formula: see text] and [Formula: see text] (wheel graph).

Authors

Institutions

Publication Details

Journal
Asian-European Journal of Mathematics
Published
2025-03-07
DOI
https://doi.org/10.1142/s1793557125500275
Primary Topic
Graph theory and applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Generalized distance spectral radius of some t-partitioned transmission regular graphs

Aditi Howlader, Pratima Panigrahi
Asian-European Journal of Mathematics
Graph theory and applications
article

Generalized distance spectral radius of some t-partitioned transmission regular graphs

Aditi Howlader, Pratima Panigrahi
article en

Abstract

Let [Formula: see text] be an [Formula: see text]-vertex connected graph with the distance matrix [Formula: see text] and the diagonal matrix of transmissions [Formula: see text]. The generalized distance matrix of a connected graph [Formula: see text] is [Formula: see text], where [Formula: see text], [Formula: see text]. Through this matrix one can study distance, distance Laplacian, distance signless Laplacian, and [Formula: see text]- spectra of [Formula: see text] in a unified way. A simple connected graph [Formula: see text] is called [Formula: see text]-partitioned transmission regular if the vertex set of [Formula: see text] can be partitioned as [Formula: see text] such that for any pair of indices [Formula: see text] (not necessarily distinct) in [Formula: see text] and [Formula: see text], [Formula: see text] is constant. In this paper, for the spider graph [Formula: see text] and the radar graph [Formula: see text], we find matrices of order [Formula: see text] (quotient matrices) corresponding to [Formula: see text] and [Formula: see text] such that the largest eigenvalues of these matrices are generalized distance spectral radius of [Formula: see text] and [Formula: see text], respectively. Moreover, we determine the full [Formula: see text]-spectrum of [Formula: see text] and [Formula: see text] (wheel graph).

Asian-European Journal of MathematicsVol. 18(09)
Indian Institute of Technology Kharagpur (IN), Indian Institute of Technology Madras (IN)
Openalex Percentile: Top 92%
Graph theory and applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.