Isomorphic relationships across complex networks

In “Network Cosmology,” a new Nature Scientific Reports paper, Dmitri Krioukov and coauthors find similarities between the growth dynamics and structures of complex networks and those of an expanding universe. Krioukov is at the Cooperative Association for Internet Data Analysis, University of California, San Diego.

From the press release:

By performing complex supercomputer simulations of the universe and using a variety of other calculations, researchers have now proven that the causal network representing the large-scale structure of space and time in our accelerating universe is a graph that shows remarkable similarity to many complex networks such as the Internet, social, or even biological networks.

From the paper:

[W]e show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology.

This research approach reminds me of the Society for General System Research and its aim (1954): “to investigate the isomorphy of concepts, laws, and models in various fields, and to help in useful transfers from one field to another.”

As described by Ludwig von Bertalanffy in General Systems Theory (1968):

A consequence of the existence of general system properties is the appearance of structural similarities or isomorphisms in different fields. There are correspondences in the principles that govern the behavior of entities that are, intrinsically, widely different. To take a simple example, an exponential law of growth applies to certain bacterial cells, to populations of bacteria, of animals or humans, and to the progress of scientific research measured by the number of publications in genetics or science in general. The entities in question, such as bacteria, animals, men (sic), books, etc., are completely different, and so are the causal mechanisms involved. Nevertheless, the mathematical law is the same.

H/t @Bigmind

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