Reading order into chaos
© Copyright 1994-2002, Rishab Aiyer Ghosh. All rights reserved.
Electric Dreams #21

If a butterfly flaps its wings in Beijing and causes storms in Alaska, can a slight drop in coffee futures indicate an impending stock market crash? Chaos theory, the popular name for the science of non-linear dynamics, is all about such deep matters. It is being, or will be used in a number of fields: from piping video over phone lines to analyzing derivatives markets to creating digital art.

Contrary to what it's called, this science is not about chaos as we normally think of it -- random uncorrelated events that cannot be made sense of -- but about highly complex, deterministic processes that can, though not without difficulty, be untangled. Chaos is about complicated systems that can be analyzed and events that can be predicted. The difference is that chaotic systems are very sensitive -- small things, like a playful butterfly somewhere, may have gigantic effects, particularly when least expected, so any prediction is rather tricky.

Chaos never repeats itself. It goes on, ever changing, like the landscape from a car window. Like most natural objects or happenings, which are always different. Different, yet similar to each other, things in nature are represented well by chaos theory.

While chaotic systems don't repeat, they get very close to doing that. They are often almost repeating. As if they have a strong, but slightly unclear memory of something that they want to do. They keep trying to do this, but don't get it quite right, slightly different each time. This 'memory' of theirs is called by mathematicians an attractor, because it's a state the system is 'attracted' to. Actually, chaotic systems usually have many attractors; the system hops whimsically from one to another leading to a profusion of similar, but always differing patterns. Because there seems no obvious reason for this behaviour, these are usually called strange attractors.

Strange attractors are present in so many things around us that examples are almost not worth giving. The Indian monsoons, regular but not quite the same as the last time; the beating of the heart, ordered but not clockwork; the whoosh of air around a supersonic jet, not without direction, but chaotic in detail. And chaos is not just visible in processes -- there are the leaves on a tree, all similar but different; the waves on the oceans or the rocky mountains, which seen close under a magnifying glass look rather like they do from afar. Researchers are using chaos theory, particularly its graphical branch to build digitized models of natural images called 'fractals' -- pictures that are generated by a chaotic system.

Scientists are working on many other uses of chaos. It could be used to improve weather forecasting, or make better stealth bombers, or make a killing on the markets, or make painless advanced pacemakers that simulate the chaotic natural heartbeats. While there is a lot of hype and mystique surrounding this field, there could be a lot of real benefits too, in the not-so-distant future.

As all natural processes -- indeed the whole universe -- are chaotic, we may be able use these new methods to provide a new depth of vision into mechanisms of the body, the world and society, and may even hope to change them. Poor butterflies.

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