Most real networks are too large or they are not available for real time analysis. Therefore, in
practice, decisions are made based on partial information about the ground truth network. It …

In this work we perform computational and analytical studies of the Randić index R (G) in
Erdös–Rényi models G (n, p) characterized by n vertices connected independently with …

A main topic in the study of topological indices is to find bounds of the indices involving
several parameters and/or other indices. In this paper we perform statistical (numerical) and …

We perform a detailed computational study of the recently introduced Sombor indices on
random networks. Specifically, we apply Sombor indices on three models of random …

Here we introduce the non-Hermitian diluted banded random matrix (nHdBRM) ensemble
as the set of N× N real nonsymmetric matrices whose entries are independent Gaussian …

Singular-value statistics (SVS) has been recently presented as a random matrix theory tool
able to properly characterize non-Hermitian random matrix ensembles [PRX Quantum 4 …

Previous literature on random matrix and network science has traditionally employed
measures derived from nearest-neighbor level spacing distributions to characterize the …

Applied network science often involves preprocessing network data before applying a
network-analysis method, and there is typically a theoretical disconnect between these …

The eigenvalue statistics are an important tool to capture localization to delocalization
transition in physical systems. Recently, a β-Gaussian ensemble is being proposed as a …

In this work, we study the effects of geometric confinement on the point statistics in a quasi-
low-dimensional system. Specifically, we focus on the nearest-neighbor statistics …