5 citations · 5 across the 26 of their papers we have counts for
27 papers
The switching conjecture for main eigenvalues is asymptotically true
Saieed Akbari, Hitesh Kumar, Bojan Mohar +1
An eigenvalue of a signed graph is called \emph{main} if there exists a corresponding eigenvector non-orthogonal to the all-ones vector. An important result of O'Rourke and Touri (…
A Vertex-Localized Positive Square-Energy Strengthening of Turán's Theorem
Abhay Jayarajan, M. Rajesh Kannan, Shivaramakrishna Pragada +1
Let be a graph of order with the adjacency eigenvalues . Let denote the maximum order of a clique containing vertex . We prove the…
Resolution of a problem of Mohar on non-positive inertia
Clive Elphick, Hitesh Kumar, Shivaramakrishna Pragada +1
For a graph of order , its positive, negative and non-positive inertia is the number of positive, negative and non-positive eigenvalues of its adjacency matrix , respe…
Stability of maximal relative projection constants
Hitesh Kumar, Bojan Mohar, Seyed Ahmad Mojallal +1
For positive integers , let denote the \emph{maximal relative projection constant} of -dimensional subspaces of and denote the \emph{maxi…
Localization of the Caro-Wei bound and its applications to bipartiteness
Aida Abiad, Hitesh Kumar, Shivaramakrishna Pragada
We confirm a conjecture of Brause, Randerath, Rautenbach and Schiermeyer (2016) by proving a localized lower bound on the independence number of a graph that strengthens the classi…
Extremal graphs for the -th eigenvalue
Hitesh Kumar, Bojan Mohar, Seyed Ahmad Mojallal +1
For a simple graph of order , let denote its adjacency eigenvalues. Hong's problem asks for the optimal upper bound for . A recent theo…
Energy and independence number
Hitesh Kumar, Shivaramakrishna Pragada
For a graph of order , with adjacency eigenvalues , the \emph{energy} of is defined to be \[\mathcal{E}(G)=\sum_{i=1}^{n} |λ_i(G)|.\] A w…
An improved bound for the strong clique index of graphs
Hitesh Kumar, Bojan Mohar, Shivaramakrishna Pragada
For a graph with line graph , and are called the \emph{strong chromatic index} and \emph{strong clique index} of , respectively. A well-known c…
Spectral Radius, Vertex Deletion, and Chromatic Number of Signed Graphs
Abhay Jayarajan, M. Rajesh Kannan, Priti Prasanna Mondal +1
A signed graph is a graph with edges given signs or defined by the function . The adjacency matrix of is defined as per these signs. The relation betw…
Localized Turán-type inequalities for -index
M. Rajesh Kannan, Hitesh Kumar, Shivaramakrishna Pragada
For a connected graph \(G\), let denote the -index of , i.e., the largest eigenvalue of its signless Laplacian matrix. Abreu and Nikiforov (2013) showed that \[ q(G) \…
Maximum spectral sum of graphs
Hitesh Kumar, Lele Liu, Hermie Monterde +2
For a graph of order , the spectral sum of is defined to be the sum , where (resp. ) is the largest (resp. second largest) adjacency ei…
Convex combination of first and second eigenvalues of trees
Hitesh Kumar, Bojan Mohar, Shivaramakrishna Pragada +1
For a graph , let and denote the largest and the second largest adjacency eigenvalue of . The sum is called the \emph{spectral sum} of …
Localization of spectral Turán-type theorems
M. Rajesh Kannan, Hitesh Kumar, Shivaramakrishna Pragada
Let be a graph, and let and be a vertex and an edge of , respectively. Define (resp. ) to be the order of the largest clique in containing (resp…
Improved Bounds for the Ultimate Independence Ratio of Odd Wheels
Alexander Clow, Hitesh Kumar, Shivaramakrishna Pragada
The ultimate independence ratio of a graph is defined as where is the independence…
A new conjecture on the inertia of graphs
Saieed Akbari, Clive Elphick, Hitesh Kumar +2
Let be a graph with adjacency matrix . We conjecture that \[2n^+(G) \le n^-(G)(n^-(G) + 1),\] where and denote the number of positive and negative eigen…
Refinement of a conjecture on positive square energy of graphs
Saieed Akbari, Hitesh Kumar, Bojan Mohar +2
Let be a simple graph of order with eigenvalues . Define \[s^+(G)=\sum_{λ_i >0} λ_i^2(G), \quad s^-(G)=\sum_{λ_i<0} λ_i^2(G).\] It was conjec…
Vertex Partitioning and -Energy of Graphs
Saieed Akbari, Hitesh Kumar, Bojan Mohar +1
For a Hermitian matrix of order with eigenvalues , define \[ \mathcal{E}_p^+(A)=\sum_{λ_i > 0} λ_i^p(A), \quad \mathcal{E}_p^-(A)=\sum_{λ_i<0} |…
A Linear Lower Bound for the Square Energy of Graphs
Saieed Akbari, Hitesh Kumar, Bojan Mohar +1
Let be a graph of order with eigenvalues . Let \[s^+(G)=\sum_{λ_i>0} λ_i^2, \qquad s^-(G)=\sum_{λ_i<0} λ_i^2.\] The smaller value, $s(G)=\min\{s^+(…
On the second largest adjacency eigenvalue of trees with given diameter
Hitesh Kumar, Bojan Mohar, Shivaramakrishna Pragada +1
For a graph , let denote the second largest eigenvalue of the adjacency matrix of . We determine the extremal trees with maximum/minimum adjacency eigenvalue i…
Bollobás-Nikiforov Conjecture for graphs with not so many triangles
Hitesh Kumar, Shivaramakrishna Pragada
Bollobás and Nikiforov conjectured that for any graph with edges \[ λ_1^2+λ_2^2\le \bigg( 1-\frac{1}{ω(G)}\bigg)2m\] where and denote the two largest e…
Constructing cospectral graphs by unfolding non-bipartite graphs
M. Rajesh Kannan, Shivaramakrishna Pragada, Hitesh Wankhede
In 2010, Butler introduced the unfolding operation on a bipartite graph to produce two bipartite graphs, which are cospectral for the adjacency and the normalized Laplacian matrice…
Subdivision and Graph Eigenvalues
Hitesh Kumar, Bojan Mohar, Shivaramakrishna Pragada +1
This paper investigates the asymptotic nature of graph spectra when some edges of a graph are subdivided sufficiently many times. In the special case where all edges of a graph are…
Signed spectral Turań type theorems
M. Rajesh Kannan, Shivaramakrishna Pragada
A signed graph is a graph where the function assigns either or to each edge of the simple graph . The adjacency matrix of , denoted by , is def…
On the construction of cospectral nonisomorphic bipartite graphs
M. Rajesh Kannan, Shivaramakrishna Pragada, Hitesh Wankhede
In this article, we construct bipartite graphs which are cospectral for both the adjacency and normalized Laplacian matrices using partitioned tensor product. This extends the cons…