  Generic quantum search algorithm searches for target entity in an unsorted
database by repeatedly applying canonical Grover's quantum rotation transform
to reach near the vicinity of the target entity. Thus, upon measurement, there
is a high probability of finding the target entity. However, the number of
times quantum rotation transform is to be applied for reaching near the
vicinity of the target is a function of the number of target entities present
in an unsorted database, which is generally unknown. A wrong estimate of the
number of target entities can lead to overshooting or undershooting the
targets, thus reducing the success probability. Some proposals have been made
to overcome this limitation. These proposals either employ quantum counting to
estimate the number of solutions or fixed-point schemes. This paper proposes a
new scheme for stopping the application of quantum rotation transformation on
reaching near the targets by disentanglement, measurement and subsequent
processing to estimate the distance of the state vector from the target states.
It ensures a success probability, which is greater than half for all
practically significant ratios of the number of target entities to the total
number of entities in a database. The search problem is trivial for remaining
possible ratios. The proposed scheme is simpler than quantum counting and more
efficient than the known fixed-point schemes. It has same order of
computational complexity as canonical Grover`s search algorithm but is slow by
a factor of two and requires two additional ancilla qubits.
