j_bertolotti,
@j_bertolotti@mathstodon.xyz avatar


The Lorenz system is a common example of chaotic dynamics and of a strange attractor.
Points with very similar initial conditions initially evolve very similarly to each other, until their trajectories diverge from each other, and start moving on a "butterfly"-shaped fractal.

Trajectories of a number of points following the Lorenz system equations, rendered as yellow tubes.

bleuje,
@bleuje@mastodon.social avatar

@j_bertolotti if you used approximations with a numerical method to draw these curves, aren't the approximation errors very much impacting the curves after some time because it's chaotic? I've often wondered about that

j_bertolotti,
@j_bertolotti@mathstodon.xyz avatar

@bleuje Yes, but you can track the error and stop when it becomes unacceptably large.

narain,
@narain@mathstodon.xyz avatar

@j_bertolotti @bleuje But Etienne is correctly concerned that in chaotic dynamics, the error grows exponentially with time, so you would have to stop very quickly! A more relevant result is the shadowing lemma:

"Although a numerically computed chaotic trajectory diverges exponentially from the true trajectory with the same initial coordinates, there exists an errorless trajectory with a slightly different initial condition that stays near ("shadows") the numerically computed one. Therefore, the fractal structure of chaotic trajectories seen in computer maps is real."

https://mathworld.wolfram.com/ShadowingTheorem.html
http://www.scholarpedia.org/article/Shadowing

j_bertolotti,
@j_bertolotti@mathstodon.xyz avatar

@narain
Then I misunderstood the question 😉
@bleuje

bleuje,
@bleuje@mastodon.social avatar

@j_bertolotti @narain I appreciate both of your answers!

j_bertolotti,
@j_bertolotti@mathstodon.xyz avatar

Released into the and uploaded to Wikimedia Commons together with the script used to generate it: https://commons.wikimedia.org/wiki/File:Lorenz_System_Lyapunov_time.webm

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