The chaos evokes images of dinosaurs running wild in Jurassic Park, or my friend’s kid ravaging the living room.
In a chaotic world, you never know what to expect. Stuff is happening all the time, driven by some kind of random impulse.
But chaos has a deeper meaning in physics and climatology, concerned with how some systems – such as the weather or child behavior – are fundamentally unpredictable.
Scientists define chaos as the amplified effects of small changes in the present moment that lead to long-term unpredictability. Picture two almost identical story. In one version, two people bump into each other in a train station; But in the second the train arrives 10 seconds earlier and the meeting never takes place. Since then, the two plot lines may have been completely different.
Usually those small details don’t matter, but sometimes small differences result in things that keep getting complicated. And that compounding leads to chaos.
A startling series of discoveries in the 1960s and ’70s showed how easy it is to create chaos. Nothing could be more predictable than the swinging pendulum of Grandpa’s clock. But if you separate a pendulum halfway down by adding another axle, swinging becomes wildly unpredictable.
Chaos is different from random
As a complex systems scientist, I think about the random a lot.
What is the difference between a deck of cards and a season?
You can’t predict your next poker hand – if you can, they’ll kick you out of the casino – while you can probably predict tomorrow’s weather. But what about the weather two weeks from now? Or a year from now?
Randomness, such as cards or dice, is unpredictable because we do not have accurate information. The chaos is somewhere between random and predictable. A hallmark of chaotic systems is predictability in the short run that breaks down quickly over time, such as in river rapids or ecosystems.
Why chaos theory matters
Isaac Newton saw physics as a set of rules governing a clockwork universe – rules that, once set in motion, would lead to a predetermined outcome. But chaos theory proves that even the strictest rules and nearly perfect information can lead to unpredictable results.
This realization has practical applications for deciding what kinds of things are exactly predictable. The chaos is why no weather app can tell you the weather two weeks from now – it’s impossible to know.
On the other hand, broad predictions may still be possible. We can’t predict the weather a year from now, but we still know what the weather is like at this time of year. In this way the climate can be predicted even when there is no weather. Theories of chaos and randomness help scientists figure out which types of predictions make sense and which do not.
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