Lifting gradient flows

In the previous post we talked about creating attracting manifolds and how to get the corresponding vector field given a manifold. In this one, we talk about optimization. Suppose we have g : &#x0211D; &#x02192; &#x0211D; for which we want to find a minimum and g is sufficiently smooth. For example, we can consider def g(x): return 0.25 * (x * x - 1.0) ** 2 + 0.18 * x That's a simple function with…