  Grover's algorithm, orginally conceived as a means of searching an unordered
database, can also be used as a technique for extracting solutions from the
result sets generated by quantum computations. The algorithm exploits the
concept of an oracle function, which abstracts the process of matching a search
item (returning 1 for a match and 0 otherwise). This black-box approach hides
the details of a search problem and works with the assumption that the items in
the search space are completely unordered. In this case, searching for 1 target
item in a search space of size $N$ scales as $\mathcal{O}(\sqrt{N})$ oracle
queries (or $\mathcal{O}(\sqrt{N/M})$ oracle queries for $M$ target items in a
search space of size $N$). Hidden inside the typical black-box oracle, however,
the process of matching an item usually involves matching multiple data bits.
In this article, we explore the idea of associating a separate oracle with each
bit of the matching condition, obtaining multiple partial oracle functions
which can be tested independently. Exploring this idea leads to a multi-stage
hybrid search algorithm, whose performance can fall within a wide range,
anywhere between $\mathcal{O}(\sqrt{N})$ (same as Grover) or
$\mathcal{O}(\log(N))$ (exponentially faster). Apparently, the search
acceleration works by dynamically discovering order in the search space, where
the order consists of correlations between the partial oracle functions and the
search index. This new algorithm is validated against the simplest kind of
search scenario.
