Scientists develop new high-precision method for analysing and comparing functioning and structure of complex networks

February 22, 2017
Credit: Universitat Politècnica de Catalunya (UPC)

Researchers at the Universitat Politècnica de Catalunya (UPC) and the University of Barcelona (UB) published a paper in Nature Communications presenting a scientific method for identifying, comparing and precisely determining objective differences between large nodes of complex networks.

The new method makes it possible, for example, to compare and differentiate the functioning of brain networks in drug addicts and healthy individuals, thus advancing the study of the symptoms and effects of addiction on the brain. The method can also be used to more effectively analyse the functioning of critical , such as power distribution networks, airport connections and even social networks like Facebook and Twitter.

Researcher Cristina Masoller explained the advantages of the new approach: "Imagine you have a power distribution system consisting of two interconnected networks, each with the same number of links, and one loses a link because of a breakdown. With the methods we've had up until now, it's only been possible to determine the difference due to that missing link. With our method, we can also determine the precise location of the lost link and its importance in relation to the system—that is, whether its absence will significantly hinder the distribution of power."

Currently, it is very difficult to differentiate, distinguish and compare the functioning and structure of networks that have hundreds of thousands of interconnected nodes and form so-called complex systems. This is true of and connections. Understanding their structures, determining differences between connections and diagnosing dysfunctions are complex tasks. Until now, there was no precise and effective way to recognise the presence or absence of critical links that connect or disconnect network components, because if they are not identified, it is difficult to ensure that they are functioning properly in the transmission of information.

According to Masoller, "That's why our method is a significant advance in the study of complex systems. It indicates, with a high degree of precision, how important failed connections are in relation to the functioning of a complex system." In addition to identifying and naming the nodes in a network, "We can reliably calculate the distances between the points it comprises. Thanks to mathematics, we've pulled it off. Now scientists have a useful tool for studying complex systems with more certainty and precision," said the UPC researcher.

According to UB researcher Díaz-Guilera: "Our also makes it possible to find out how a particular topological feature was formed. Defining the distance between networks allows us to generate virtual networks based on specific mathematical models and see which one gets us closest to reality. Networks that expand based on geographical proximity, such as transport networks, are different from those whose growth is driven by affinity, such as social networks. Understanding how a network was formed, based on these mathematical models, allows us to determine what its strengths and vulnerabilities will be."

The methods available to the scientific community up until now could be used to detect a difference in the number of connections in a network or even to determine the number of connections that were not working, but existing methods could not be used to work out the location of damaged connections or whether they were really interrupting the flow of information in the network as a whole.

Explore further: Connections between groups of people determine the speed at which a virus spreads

More information: Tiago A. Schieber et al. Quantification of network structural dissimilarities, Nature Communications (2017). DOI: 10.1038/ncomms13928

Related Stories

Uncovering complex network structures in nature

December 10, 2014

The global spread of Ebola is due to the complex interactions between individuals, societies, and transportation and trade networks. Understanding and building appropriate statistical and mathematical models of these interactions ...

A friend of a friend is... a dense network

December 1, 2016

It's a familiar request in the digital age: one of your friends on social media has a friend who wants to be your friend. Frequent linking among friends of friends can cause a rapid increase in social network connectivity.

Why natural networks are more stable than man-made networks

September 25, 2014

(Phys.org) —Interconnected natural networks, such as the ones formed by neurons in the brain, are known to be more stable and resilient to failure than networks created by humans, such as the Internet. Now, a group of international ...

Inter-dependent networks stress test

August 28, 2014

Energy production systems are good examples of complex systems. Their infrastructure equipment requires ancillary sub-systems structured like a network—including water for cooling, transport to supply fuel, and ICT systems ...

Recommended for you

New method analyzes corn kernel characteristics

November 17, 2017

An ear of corn averages about 800 kernels. A traditional field method to estimate the number of kernels on the ear is to manually count the number of rows and multiply by the number of kernels in one length of the ear. With ...

Optically tunable microwave antennas for 5G applications

November 16, 2017

Multiband tunable antennas are a critical part of many communication and radar systems. New research by engineers at the University of Bristol has shown significant advances in antennas by using optically induced plasmas ...

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.