I understand the basics of minimax and alpha-beta pruning. In all the literature, they talk about the time complexity for the best case is O(b^(d/2)) where b = branching factor and d = depth of the tree, and the base case is when all the preferred nodes are expanded first.

In my example of the "best case", I have a binary tree of 4 levels, so out of the 16 terminal nodes, I need to expand at most 7 nodes. How does this relate to O(b^(d/2))?

I don't understand how they come to O(b^(d/2)).

Please, can someone explain it to me? Thanks a lot!