Via VC Blog
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By Manuel Lima
In the end of many of my talks, after going through a variety of compelling examples of network visualization, I wrap up with a bit of a quandary, asking the audience if there’s such a thing as a universal structure. This teaser usually comprises a side-by-side comparison between a mouse’s neuronal network and a simulation of the growth of cosmic structure and the formation of galaxies and quasars.

A common juxtaposition, shown during many of my lectures, between a neuronal network (left) and the vast cosmic structure (right).
As it turns out, this inquiry might not be as far-fetched as we might think. A few days ago, National Geographic posted an intriguing article titled Astronomers Get First Glimpse of Cosmic Web, where they report how scientists have for the first time captured a peek of the “vast, web-like network of diffuse gas that links all of the galaxies in the cosmos.” As stated in the article:
Leading cosmological theories suggest that galaxies are cocooned within gigantic, wispy filaments of gas. This “cosmic web” of gas-filled nebulas stretches between large, spacious voids that are tens of millions of light years wide. Like spiders, galaxies mostly appear to lie within the intersections of the long-sought webs.

From the original image caption in the article: Computer simulations suggest that matter in the universe is distributed in a “cosmic web” of filaments, as seen in the image above from a large-scale dark-matter simulation. The inset is a zoomed-in, high-resolution image of a smaller part of the cosmic web, 10 million light-years across, from a simulation that includes gas as well as dark matter. The intense radiation from a quasar can, like a flashlight, illuminate part of the surrounding cosmic web (highlighted in the image) and make a filament of gas glow, as was observed in the case of quasar UM287. Credit: Anatoly Klypin and Joel Primack, S. Cantalupo
This find is not just impressive and thought-provoking, but it could also become a major focus of the emerging fields of complex systems and network science.