These are exciting times for quantum physics as new quantum technologies are expected to
soon transform computing at an unprecedented level. Simultaneously network science is …

This survey seeks to describe methods for measuring the entropy of graphs and to
demonstrate the wide applicability of entropy measures. Setting the scene with a review of …

Chromatin architecture, a key regulator of gene expression, can be inferred using chromatin
contact data from chromosome conformation capture, or Hi-C. However, classical Hi-C does …

In this paper we explore how the von Neumann entropy can be used as a measure of graph
complexity. We also develop a simplified form for the von Neumann entropy of a graph that …

Entropy metrics (for example, permutation entropy) are nonlinear measures of irregularity in
time series (one-dimensional data). Some of these entropy metrics can be generalised to …

Quantifying the complexity of ecological networks has remained elusive. Primarily,
complexity has been defined on the basis of the structural (or behavioural) complexity of the …

In the present work we intend to investigate how to detect the behaviour of the immune
system reaction to an external stimulus in terms of phase transitions. The immune model …

In this paper, we develop the notion of entropy for uniform hypergraphs via tensor theory. We
employ the probability distribution of the generalized singular values, calculated from the …

Protein–protein interaction networks have been used to investigate the influence of SARS-
CoV-2 viral proteins on the function of human cells, laying out a deeper understanding of …

Graph sparsification aims to reduce the number of edges of a graph while maintaining its
structural properties. In this paper, we propose the first general and effective information …