Proceedings

EPJ B Highlight - Physicists with green fingers estimate tree spanning rate in random networks

The diagram of the random network model.

A team in China has just calculated the size of scale-free and small-world networks

Networks are often described as trees with spanning branches. How the tree branches out depends on the logic behind the network’s expansion, such as random expansion. However, some aspects of such randomly expanding networks are invariant; in other words, they display the same characteristics, regardless of the network’s scale. As a result, the entire network has the same shape as one or more of its parts. In a new study published in EPJ B, Fei Ma from Northwest Normal University in Lanzhou, Gansu Province, China, anc colleagues calculate the total number of spanning trees in randomly expanding networks. This method can be applied to modelling scale-free network models, which, as it turns out, are characterised by small-world properties. This means, for instance, that members of the network only exhibit six degrees of separation, like most people in our society.

Previously, a number of network models were based on graphs consisting of an aggregation of vertices with connecting edges. But they were not sufficient to model real-life networks, like networks of social media users. Instead, complex networks, where the network is created randomly, have become the mainstays of computer science and modern discrete mathematics. Using data from real-life networks, and drawing on the experience gained from artificial networks created to account for specific functions, the authors design more realistic models that are more complex than their predecessors.

In this study, the authors focus on developing a recursive method for calculating the number of spanning trees in a network, which is particularly helpful for predicting its capacity to tolerate faults that occur at random. Being able to find the number of spanning trees in network models has implications for various scientific fields, such as applied mathematics, theoretical computer science, physics and chemistry.

This was our first experience of publishing with EPJ Web of Conferences. We contacted the publisher in the middle of September, just one month prior to the Conference, but everything went through smoothly. We have had published MNPS Proceedings with different publishers in the past, and would like to tell that the EPJ Web of Conferences team was probably the best, very quick, helpful and interactive. Typically, we were getting responses from EPJ Web of Conferences team within less than an hour and have had help at every production stage.
We are very thankful to Solange Guenot, Web of Conferences Publishing Editor, and Isabelle Houlbert, Web of Conferences Production Editor, for their support. These ladies are top-level professionals, who made a great contribution to the success of this issue. We are fully satisfied with the publication of the Conference Proceedings and are looking forward to further cooperation. The publication was very fast, easy and of high quality. My colleagues and I strongly recommend EPJ Web of Conferences to anyone, who is interested in quick high-quality publication of conference proceedings.

On behalf of the Organizing and Program Committees and Editorial Team of MNPS-2019, Dr. Alexey B. Nadykto, Moscow State Technological University “STANKIN”, Moscow, Russia. EPJ Web of Conferences vol. 224 (2019)

ISSN: 2100-014X (Electronic Edition)

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