I am currently looking at the Lorenz Attractor and I am curious to why I get this peculiar result.
So first of all my understanding is that by using: sigma = 10, rho = 28, and sigma = 8/3 this system of equations gives us the butterfly chaotic attractor.
So we can consistently recreate the same attractor lets add a seed of 9 to the ensemble.
When we run the tutorial as it is with 2000 neurons we get a butterfly attractor.
If we reduce it to 500 we can still get a butterfly attractor.
However if we increase it to 1000 neurons we get a fixed point attractor and if we go to 4000 neurons we get a another fixed point attractor.
Why does an increase in neurons create a worse/wrong representation of the butterfly attractor?