  We study the limit computability of finding a global optimum of a continuous
function. We give a short proof to show that the problem of checking whether a
point is a global minimum is not limit computable. Thereby showing the same for
the problem of finding a global minimum. In the next part, we give an algorithm
that converges to the global minima when a lower bound on the size of the basin
of attraction of the global minima is known. We prove the convergence of this
algorithm and provide some numerical experiments.
