Use Quantum Computing Finding the Minimum (In Progress)

 

1. OverviewThe Quantum Minimum Search algorithm is a technique used to find the minimum value in a set of data. It works by using an Oracle function to identify states whose value is below a thresh...

1. Overview

The Quantum Minimum Search algorithm is a technique used to find the minimum value in a set of data. It works by using an Oracle function to identify states whose value is below a threshold, and then using the Grover Operator to increase the amplitude of these states. The measurement of the resulting state will result in a smaller value than the previous threshold, and the process is repeated until the minimum value is found.

2. Algorithm Workflow

QUANTUM MINIMUM SEARCHING ALGORITHM

  1. Choose threshold index \(0 \leq y \leq N-1\) uniformly at random.
  2. Repeat the following and interrupt it when the total running time is more than \(22.5 \sqrt{N}+\) \(1.4 \lg ^{2} N .{ }^{1}\) Then go to stage \(2(2 \mathrm{c})\). (a) Initialize the memory as \(\sum_{j} \frac{1}{\sqrt{N}}|j\rangle|y\rangle\) . Mark every item \(j\) for which \(T[j]<T[y]\). (b) Apply the quantum exponential searching algorithm of [2]. (c) Observe the first register: let \(y^{\prime}\) be the outcome. If \(T\left[y^{\prime}\right]<T[y]\), then set threshold index \(y\) to \(y^{\prime}\).
  3. Return \(y\).

2.1 How to determine the times of rotations?

The quantum exponential search algorithm will return one of the marked entries with equal probability after an expected number of \(\mathcal{O}(\sqrt{N / t})\) iterations if there are \(t \geq 1\) marked entries. If there are no marked entries, the algorithm will run indefinitely. The algorithm has a running time of \(\mathcal{O}(\sqrt{N})\) and will find the index of the minimum value with a probability of at least \(\frac{1}{2}\).


Qiskit Implementation Here

To be updated —

3. Qiskit Overall Circuit

To be updated

Reference:

1. Nielsen, Michael A., and Isaac Chuang. "Quantum computation and quantum information." (2002): 558-559.

2. C. Durr and P. Hoyer, “A Quantum Algorithm for Finding the Minimum,” arXiv:quant-ph/9607014, Jan. 1999, Accessed: May 04, 2022. [Online]. Available: http://arxiv.org/abs/quant-ph/9607014

3. Y. Kang and J. Heo, “Quantum Minimum Searching Algorithm and Circuit Implementation,” in 2020 International Conference on Information and Communication Technology Convergence (ICTC), 2020, pp. 214–219. doi: 10.1109/ICTC49870.2020.9289455.