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Construction of non-isomorphic cospectral graphs is a nontrivial problem in spectral graph theory specially for large graphs. In this paper, we establish that graph theoretical partial transpose of a graph is a potential tool to create…

Combinatorics · Mathematics 2018-08-13 Supriyo Dutta , Bibhas Adhikari

The generalized distance matrix of a graph is a matrix in which the $(i,j)$th entry is a function, $f$, of the distance between vertex $i$ and vertex $j$. Depending on the choice of $f$, this family of matrices includes both the adjacency…

Combinatorics · Mathematics 2024-12-10 Ori Friesen , Cecily Kolko , Nick Layman , Kate Lorenzen , Sarah Zaske , Amy Zeigler

Let $M\circ N$ denote the Schur product of two matrices $M$ and $N$. A graph $X$ with adjacency matrix $A$ is walk regular if $A^k\circ I$ is a constant times $I$ for each $k\ge0$, and $X$ is 1-walk-regular if it is walk regular and…

Combinatorics · Mathematics 2025-01-28 Chris Godsil , Wanting Sun , Xiaohong Zhang

Two graphs are cospectral if their respective adjacency matrices have the same multiset of eigenvalues, and generalized cospectral if they are cospectral and so are their complements. We study generalized cospectrality in relation to…

Logic in Computer Science · Computer Science 2022-10-12 Aida Abiad , Anuj Dawar , Octavio Zapata

In this paper, we investigate various algebraic and graph theoretic properties of the distance matrix of a graph. Two graphs are $D$-cospectral if their distance matrices have the same spectrum. We construct infinite pairs of $D$-cospectral…

The search for a highly discriminating and easily computable invariant to distinguish graphs remains a challenging research topic. Here we focus on cospectral graphs whose complements are also cospectral (generalized cospectral), and on…

Combinatorics · Mathematics 2023-04-17 Aida Abiad , Carlos A. Alfaro , Ralihe R. Villagrán

How does coarsening affect the spectrum of a general graph? We provide conditions such that the principal eigenvalues and eigenspaces of a coarsened and original graph Laplacian matrices are close. The achieved approximation is shown to…

Machine Learning · Computer Science 2018-02-22 Andreas Loukas , Pierre Vandergheynst

We consider two types of joins of graphs $G_{1}$ and $G_{2}$, $G_{1}\veebar G_{2}$ - the Neighbors Splitting Join and $G_{1}\underset{=}{\lor}G_{2}$ - the Non Neighbors Splitting Join, and compute the adjacency characteristic polynomial,…

Combinatorics · Mathematics 2023-08-16 Suliman Hamud , Abraham Berman

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 matrices. In this article, we describe how the idea of unfolding a…

Combinatorics · Mathematics 2024-11-22 M. Rajesh Kannan , Shivaramakrishna Pragada , Hitesh Wankhede

Let $n$ be any positive integer and let $F_n$ be the friendship (or Dutch windmill) graph with $2n+1$ vertices and $3n$ edges. Here we study graphs with the same adjacency spectrum as the $F_n$. Two graphs are called cospectral if the…

Combinatorics · Mathematics 2013-07-23 Alireza Abdollahi , Shahrooz Janbaz , Mohammad Reza Oboudi

Typically, graph structures are represented by one of three different matrices: the adjacency matrix, the unnormalised and the normalised graph Laplacian matrices. The spectral (eigenvalue) properties of these different matrices are…

Methodology · Statistics 2020-01-27 J. F. Lutzeyer , A. T. Walden

We use the line digraph construction to associate an orthogonal matrix with each graph. From this orthogonal matrix, we derive two further matrices. The spectrum of each of these three matrices is considered as a graph invariant. For the…

Quantum Physics · Physics 2007-05-23 David Emms , Edwin R. Hancock , Simone Severini , Richard C. Wilson

Learning a graph with a specific structure is essential for interpretability and identification of the relationships among data. It is well known that structured graph learning from observed samples is an NP-hard combinatorial problem. In…

Machine Learning · Statistics 2019-09-26 Sandeep Kumar , Jiaxi Ying , Jos'e Vin'icius de M. Cardoso , Daniel P. Palomar

Cospectral graphs are a fascinating concept in graph theory, where two non-isomorphic graphs possess identical sets of eigenvalues. In this paper, we compute the $A_\alpha$-characteristic polynomial of neighbour and non-neighbour splitting…

Combinatorics · Mathematics 2024-03-11 Najiya V K , Chithra A

An invariant for cospectral graphs is a property shared by all cospectral graphs. In this paper, we establish three novel arithmetic invariants for cospectral graphs, revealing deep connections between spectral properties and combinatorial…

Combinatorics · Mathematics 2025-04-15 Yizhe Ji , Quanyu Tang , Wei Wang , Hao Zhang

In this paper, we introduce a matrix for a mixed graph, called the integrated adjacency matrix. This matrix uniquely determines a mixed graph, as long as the indices of the matrix are specified. Additionally, we associate an (undirected)…

Combinatorics · Mathematics 2025-11-27 G. Kalaivani , R. Rajkumar

Extending a classic result of Johnson and Newman, this paper provides a matrix characterization for two generalized cospectral graphs with a pair of generalized cospectral vertex-deleted subgraphs. As an application, we present a new…

Combinatorics · Mathematics 2024-08-06 Wei Wang , Wenqiang Wen , Songlin Guo

A connected graph can be associated with two distinct evolution algebras. In the first case, the structural matrix is the adjacency matrix of the graph itself. In the second case, the structural matrix is the transition probabilities matrix…

Combinatorics · Mathematics 2024-05-22 Paula Cadavid , Mary Luz Rodiño Montoya , Pablo M. Rodriguez , Sebastian J. Vidal

This paper establishes an upper bound on the number of generalized cospectral mates of simple graphs, where the generalized spectrum consists of the spectrum of a graph and its complement. Moving beyond the classical problem of identifying…

Combinatorics · Mathematics 2026-03-24 Muhammad Raza , Obaid Ullah Ahmad , Mudassir Shabbir , Waseem Abbas

Observational data usually comes with a multimodal nature, which means that it can be naturally represented by a multi-layer graph whose layers share the same set of vertices (users) with different edges (pairwise relationships). In this…

Machine Learning · Computer Science 2015-08-31 Xiaowen Dong , Pascal Frossard , Pierre Vandergheynst , Nikolai Nefedov