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A network science viewpoint on the National Institute of Science and Technology of Quantum Information (INCT-IQ)

Network science is a multidisciplinary field that offers a broad framework for studying statistical properties of a variety of phenomena. At the core of its success is the fact that systems, in spite of the complexity of their constituents or interactions, can be represented as a simple graph, a set of nodes connected by edges. In this approach, processes of a very different nature, such as the internet, scientific collaborations, or protein networks, become similar from a network point of view, which allows not only to understand natural networks in a unified way, but also to optimize and design more efficient artificial networks. Within this context, this article has two objectives. First, present the main concepts of network science, such as graphs, the small-world property, connectivity distribution, among others, as well as some of the main network models proposed in the literature. The second objective is to apply network science to analyze a real network, more precisely the network of researchers from the National Institute of Science and Technology of Quantum Information. Our results show that from a statistical point of view the studied network is well described by a truncated power law, with a high degree of interconnectivity among the participants. A cluster, formed by 8 smaller communities, contains 85% of the network’s scientists. The network’s average number of collaborations is close to 5 and the average of articles published is above 13 in the analyzed period of time. The network has a high clustering coefficient, with a value of C=0.4, showing that the collaborators of a given scientist also tend to collaborate with each other.

Keywords:
Complex Networks; Network Science; Quantum Information


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