  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 represented by a basis state in
the Hilbert space associated with the qubits. Thus, when qubits are measured,
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 the 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 measurement and subsequent processing to estimate
the distance of the state vector from the target states. It ensures a success
probability, which is at least greater than half for all the ratios of the
number of target entities to the total number of entities in a database, which
are less than half. 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 an additional ancilla qubit.
