An Optimized Quantum Maximum or Minimum Searching Algorithm and its
  Circuits
Finding a maximum or minimum is a fundamental building block in many
mathematical models. Compared with classical algorithms, Durr, Hoyer's quantum
algorithm (DHA) achieves quadratic speed. However, its key step, the quantum
exponential searching algorithm (QESA), which is based on Grover algorithm, is
not a sure-success algorithm. Meanwhile, quantum circuits encounter the gate
decomposition problem due to variation of the scale of data. In this paper, we
propose an optimized quantum algorithm for searching maximum and minimum, based
on DHA and the optimal quantum exact search algorithm. Furthermore, we provide
the corresponding quantum circuits, together with three equivalent
simplifications. In circumstances when we can exactly estimate the ratio of the
number of solutions M and the searched space N, our method can improve the
successful probability close to 100%. Furthermore, compared with DHA, our
algorithm shows an advantage in complexity with large databases and in the gate
complexity of constructing oracles. Experiments have been executed on an IBM
superconducting processor with two qubits, and a practical problem of finding
the minimum from Titanic passengers' age was numerically simulated. Both showed
that our optimized maximum or minimum performs more efficiently compared with
DHA. Our algorithm can serve as an important subroutine in various quantum
algorithms which involves searching maximum or minimum.
Yanhu Chen Shijie Wei Xiong Gao Cen Wang Jian Wu Hongxiang Guo