The Puzzle of How Large-Scale Order Emerges in Complex Systems
With a new framework, researchers believe they could be close to explaining how regularities emerge on macro scales out of systems made up of uncountable constituent parts.
by Philip Ball
THE ORIGINAL VERSION of this story appeared in Quanta Magazine.
A few centuries ago, the swirling polychromatic chaos of Jupiter’s atmosphere spawned the immense vortex that we call the Great Red Spot.
From the frantic firing of billions of neurons in your brain comes your unique and coherent experience of reading these words.
As pedestrians each try to weave their path on a crowded sidewalk, they begin to follow one another, forming streams that no one ordained or consciously chose.
The world is full of such emergent phenomena: large-scale patterns and organization arising from innumerable interactions between component parts. And yet there is no agreed scientific theory to explain emergence. Loosely, the behavior of a complex system might be considered emergent if it can’t be predicted from the properties of the parts alone. But when will such large-scale structures and patterns arise, and what’s the criterion for when a phenomenon is emergent and when it isn’t? Confusion has reigned. “It’s just a muddle,” said Jim Crutchfield, a physicist at the University of California, Davis.
“Philosophers have long been arguing about emergence, and going round in circles,” said Anil Seth, a neuroscientist at the University of Sussex in England. The problem, according to Seth, is that we haven’t had the right tools—“not only the tools for analysis, but the tools for thinking. Having measures and theories of emergence would not only be something we can throw at data but would also be tools that can help us think about these systems in a richer way.”