Elements S4 • E74

How Chaos Theory Unravels the Mysteries of Nature





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Published on Aug 1, 2019

Ever wonder how we try to predict the unpredictable? Supercomputers use the power of chaos theory.
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As humans, we’re always trying to know more about how our world works, so we make models, models that allow us to reasonably predict what might happen if any of the established variables in a situation were to change. This is a deterministic system, meaning the behavior of certain variables is determined by their known characteristics.

But what happens when the situation is a whole lot messier, with many, many variables and moving parts to keep track of? Take the weather for example, to make a perfect weather prediction we would have to have highly accurate measurements of every contributing variable over every single square inch of atmosphere we are looking at.

So you can imagine, any tiny change of the input could mean a huge variation in the output, and while the system is still deterministic in that the variables do behave the way we expect them to, it is still very unpredictable and subject to variation making it chaos…but with rules, a.k.a. deterministic chaos.

Deterministic chaos—you may have also heard of it as chaos theory or the butterfly effect. And, of course, weather is actually how chaos theory was first discovered by Edward Lorenz, a meteorologist at MIT, and his team in the 1960s.

Learn more about chaos theory, supercomputers, and deterministic systems on this episode of Elements.

#ChaosTheory #Supercomputer #ButterflyEffect #Seeker #Elements #Science

Is the Butterfly Effect Real?

Read More:
Chaos and the Double Pendulum
"Chaotic dynamics, in a nutshell, means that a system is extremely sensitive to initial conditions. That means a small change in where the system begins, becomes a big difference in where it ends up. A lot of people say that chaos means that we cant predict what the system will do, and this is not exactly true. Chaotic systems, including the one we are looking at today, can be deterministic."

Uncertainty in weather and climate prediction
"Early implementation of probabilistic methods for numerical weather prediction was based on applying small, random perturbations to the atmospheric state variables (temperature, humidity, winds and pressure) in the analysed initial condition."

When the Butterfly Effect Took Flight
"Lorenz was repeating a simulation he’d run earlier—but he had rounded off one variable from .506127 to .506. To his surprise, that tiny alteration drastically transformed the whole pattern his program produced, over two months of simulated weather."

Thanks to Think Twice for his amazing visualizations, go check out his channel for more: https://www.youtube.com/channel/UC9yt...


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