This is an interesting idea. I think I get the gist of it, you are essentially organizing the validators into a binary tree and performing a commit/reveal ceremony at each level of the tree. This essentially takes away the opportunity (or minimizes the likelihood) for a validator to bias the entropy bc if they choose not to reveal, then the other proposer can continue the ceremony without them.
Quick question:
If was to rerun your simulations…obviously, i need to change n and f accordingly, but it also looks like this line:
print zip(np.average(results,0),["Layer %d compromised" % i for i in range(8)] + ["Tree compromised"])
is looping through the layers of the tree and using the avg results of each trial to display the prob of the layer being compromised. I am assuming that instead of using range(8), I can just calc the number of layers like this: int(math.log(n,2)) + 1 . I just want to make sure I am understanding.