English
Related papers

Related papers: A general switching method for constructing E-cosp…

200 papers

This paper develops analityc methods for investigating uniform hypergraphs. Its starting point is the spectral theory of 2-graphs, in particular, the largest and the smallest eigenvalues of 2-graphs. On the one hand, this simple setup is…

Combinatorics · Mathematics 2013-08-14 Vladimir Nikiforov

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

In this paper, we present an equitable partition theorem of tensors, which gives the relations between $H$-eigenvalues of a tensor and its quotient equitable tensor and extends the equitable partitions of graphs to hypergraphs. Furthermore,…

Combinatorics · Mathematics 2018-09-18 Ya-Lei Jin , Jie Zhang , Xiao-Dong Zhang

This paper proposes a family of permutation-invariant graph embeddings, generalizing the Skew Spectrum of graphs of Kondor & Borgwardt (2008). Grounded in group theory and harmonic analysis, our method introduces a new class of graph…

Machine Learning · Computer Science 2025-05-30 Armando Bellante , Martin Plávala , Alessandro Luongo

In this article we are introducing combinatorial spectra of graphs, this is a generalization of $H$-Hamiltonian spectra. The main motivation was to made from $H$-Hamiltonian spectra an operation and develop some algebra in this field. An…

Combinatorics · Mathematics 2023-11-21 Martin Dzúrik

Local operations of combinatorial structures (graphs, Hadamard matrices, codes, designs) that maintain the basic parameters unaltered, have been widely used in the literature under the name of switching. We show an equivalence between two…

Combinatorics · Mathematics 2024-10-15 Aida Abiad , Louka Peters

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

Here we study the spectral properties of an underlying weighted graph of a non-uniform hypergraph by introducing different connectivity matrices, such as adjacency, Laplacian and normalized Laplacian matrices. We show that different…

Combinatorics · Mathematics 2019-03-28 Anirban Banerjee

We give some graph theoretical formulas for the trace $Tr_k(\mathbb {T})$ of a tensor $\mathbb {T}$ which do not involve the differential operators and auxiliary matrix. As applications of these trace formulas in the study of the spectra of…

Spectral Theory · Mathematics 2013-07-23 Jia-Yu Shao , Liqun Qi , Shenglong Hu

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

These notes offer a unified introduction to spectral methods for the study of complex systems. They are intended as an operative manual rather than a theorem-proof textbook: the emphasis is on tools, identities, and perspectives that can be…

Statistical Mechanics · Physics 2025-09-10 Francesco Caravelli

Let p be a singular point of a variety. Consider a resolution where the preimage of p is a simple normal crossing divisor E. The combinatorial structure of E is described by a cell complex D(E), called the dual graph or dual complex of E.…

Algebraic Geometry · Mathematics 2012-03-14 János Kollár

A graph $G$ is said to be determined by its generalized spectrum (DGS for short) if for any graph $H$, $H$ and $G$ are cospectral with cospectral complements implies that $H$ is isomorphic to $G$. It turns out that whether a graph $G$ is…

Combinatorics · Mathematics 2014-10-22 Wei Wang

Several researchers have recently explored various graph parameters that can or cannot be characterized by the spectrum of a matrix associated with a graph. In this paper we show that several NP-hard zero forcing numbers are not…

Combinatorics · Mathematics 2022-04-25 Aida Abiad , Boris Brimkov , Jane Breen , Thomas R. Cameron , Himanshu Gupta , Ralihe R. Villagrán

As a powerful tool for modeling complex relationships, hypergraphs are gaining popularity from the graph learning community. However, commonly used frameworks in deep hypergraph learning focus on hypergraphs with edge-independent vertex…

Machine Learning · Computer Science 2022-07-26 Jiying Zhang , Fuyang Li , Xi Xiao , Tingyang Xu , Yu Rong , Junzhou Huang , Yatao Bian

Determining whether two graphs are structurally identical is a fundamental problem with applications spanning mathematics, computer science, chemistry, and network science. Despite decades of study, graph isomorphism remains a challenging…

Computational Physics · Physics 2026-04-10 Sara Najem , Amer E. Mouawad

The purpose of this paper is to introduce a model to study structures which are widely present in public transportation networks. We show that, through hypergraphs, one can describe these structures and investigate the relation between…

Combinatorics · Mathematics 2020-05-18 Eleonora Andreotti

The Harary-Sachs theorem for $k$-uniform hypergraphs equates the codegree-$d$ coefficient of the adjacency characteristic polynomial of a uniform hypergraph with a weighted sum of subgraph counts over certain multi-hypergraphs with $d$…

Combinatorics · Mathematics 2021-07-23 Gregory J. Clark , Joshua Cooper

In this paper, we investigate spectral properties of the adjacency tensor, Laplacian tensor and signless Laplacian tensor of general hypergraphs (including uniform and non-uniform hypergraphs). We obtain some bounds for the spectral radius…

Combinatorics · Mathematics 2016-05-20 Changjiang Bu , Jiang Zhou , Lizhu Sun

We investigate graph representation learning approaches that enable models to generalize across graphs: given a model trained using the representations from one graph, our goal is to apply inference using those same model parameters when…

Machine Learning · Computer Science 2023-02-20 Anton Amirov , Chris Quirk , Jennifer Neville