  We generalize Grover's unstructured quantum search algorithm to enable it to
use an arbitrary starting superposition and an arbitrary unitary matrix
simultaneously. We derive an exact formula for the probability of the
generalized Grover's algorithm succeeding after n iterations. We show that the
fully generalized formula reduces to the special cases considered by previous
authors. We then use the generalized formula to determine the optimal strategy
for using the unstructured quantum search algorithm. On average the optimal
strategy is about 12% better than the naive use of Grover's algorithm. The
speedup obtained is not dramatic but it illustrates that a hybrid use of
quantum computing and classical computing techniques can yield a performance
that is better than either alone. We extend the analysis to the case of a
society of k quantum searches acting in parallel. We derive an analytic formula
that connects the degree of parallelism with the optimal strategy for
k-parallel quantum search. We then derive the formula for the expected speed of
k-parallel quantum search.
