A team of physicists has conducted an investigation to understand how complex behaviors emerge from seemingly simple networks in the hopes of one day controlling them.

In the 1600s, Dutch scientist Christiaan Huygens discovered that two pendulum clocks placed on the same wooden case will always oscillate in synchronicity. To this day, similar behaviors can be observed anywhere from fireflies and the heart cells to power grids.

However, how networks with identical elements fall out of sync remains a mystery. Researchers believe that understanding self-organizing behaviors among simple networks could lead to the creation of tools that can nudge them back into rhythm when they fall out of sync.

Their findings appear in the journal Science.

Understanding How Simple Networks Synchronize

"Societal operation is based on networks, from transportation, communication and power grid networks, to social and economic networks. Each of these networks already displays behaviors beyond our understanding, yet we need them to work seamlessly together," explained Raissa D'Souza, a professor at University of California, Davis. "Perhaps we can exploit that interdependence."

For the investigation, the researchers used an experimental network developed by Michael L. Roukes and colleagues at the California Institute of Technology based on nanoelectromechanical system (NEMS) oscillators. They began by connecting two, but they eventually moved on to eight NEMS oscillators.

To their surprise, the eight-node system evolved into various complex states. James Crutchfield, a professor of physics at UC Davis and a study author, stated that this is the first experiment to demonstrate the distinct and complex states that can occur within the same simple system.

They described the behavior to Rockette dancers where every other dancer is kicking a leg up after the dancers in between are doing something completely different like waving their hats around.

"The perplexing feature of these particular states is that the Rockettes in our metaphor can only see their nearest neighbor, yet manage to be coordinating with their neighbor's neighbor," explained Matthew Matheny, a research scientist from Caltech and the lead author of the study.

The Investigation Continues

However, their work is not done yet. The researchers are hoping to build increasingly complex networks to observe how it will behave.

They added that understanding the mechanism that influences how the networks will evolve over time will allow them to precisely control how the networks function. Eventually, they might even apply their findings to one of the most complex networks ever — the human brain.