Nonadiabatic Quantum Search Algorithm with Analytical Success Rate

2018 ◽  
Vol 58 (3) ◽  
pp. 939-949
Author(s):  
Feng-Guang Li ◽  
Wan-Su Bao ◽  
Tan Li ◽  
He-liang Huang ◽  
Shuo Zhang ◽  
...  
Keyword(s):  
Success Rate ◽  
Search Algorithm ◽  
Quantum Search ◽  
Quantum Search Algorithm

Optimization of 16-Element Quantum Search on IBMQ

SPIN ◽  
2021 ◽  
pp. 2140003
Author(s):  
Wei Zi ◽  
Shuai Yang ◽  
Cheng Guo ◽  
Xiaoming Sun
Keyword(s):  
Success Rate ◽  
Search Algorithm ◽  
Quantum Circuit ◽  
Experimental Results ◽  
Quantum Search ◽  
Quantum Devices ◽  
Grover Algorithm ◽  
Quantum Search Algorithm ◽  
Diffusion Operator ◽  
And Diffusion

Unstructured searching, which is to find the marked element from a given unstructured data set, is a widely studied problem in computer science. It is well known that Grover algorithm provides a quadratic speedup to solve unstructured search problem compared with the classical algorithm. This algorithm has received a lot of attention due to the strong versatility. In this manuscript, we report experimental results of searching a unique target from 16 elements on five different quantum devices of IBM quantum Experience (IBMQ). We first implement the original Grover algorithm on these devices. However, the experiment probability of success of finding the correct target is almost the same as random choice. We then optimize the quantum circuit size of the search algorithm. The oracle operator and diffusion operator are two of the most costly operators in Grover algorithm. For the 16-element quantum search algorithm, both the oracle operator and diffusion operator consist of a triple controlled [Formula: see text] gate ([Formula: see text]) and some single-qubit gates. So we optimize the implementation of the [Formula: see text] gate according to the qubits layout of different quantum devices. On the ibmq_santiago, the experimental success rate of the 16-element quantum search algorithm is increased to [Formula: see text] by the optimization, which is better than all the published experiments implemented on IBMQ devices. For other IBMQ devices, the experimental success rate of 16-element quantum search also has been significantly improved. We then try to further reduce the size of the quantum circuit by modifying the Grover algorithm, with a tolerable loss of the theoretical success probability. On ibmq_quito, the experimental success rate is further improved from 25.23% to 27.56% after optimization. These experimental results show the importance of circuit optimization and algorithm optimization in the Noisy-Intermediate-Scale Quantum (NISQ) era.

Success Rate Versus Finite Run Time in Local Adiabatic Quantum Search Algorithm

2017 ◽  
Vol 67 (4) ◽  
pp. 355 ◽  
Author(s):  
Feng-Guang Li ◽  
Wan-Su Bao ◽  
Xiang Wang ◽  
Xiang-Qun Fu ◽  
Shuo Zhang ◽  
...  
Keyword(s):  
Success Rate ◽  
Search Algorithm ◽  
Quantum Search ◽  
Quantum Search Algorithm ◽  
Rate Versus ◽  
Run Time

scholarly journals Robust Quantum Search with Uncertain Number of Target States

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1649
Author(s):  
Yuanye Zhu ◽  
Zeguo Wang ◽  
Bao Yan ◽  
Shijie Wei
Keyword(s):  
Success Rate ◽  
Search Algorithm ◽  
Quantum Algorithms ◽  
Query Complexity ◽  
Quantum Search ◽  
Success Rates ◽  
Quantum Search Algorithm ◽  
Speed Up ◽  
Target States ◽  
Marked State

The quantum search algorithm is one of the milestones of quantum algorithms. Compared with classical algorithms, it shows quadratic speed-up when searching marked states in an unsorted database. However, the success rates of quantum search algorithms are sensitive to the number of marked states. In this paper, we study the relation between the success rate and the number of iterations in a quantum search algorithm of given λ=M/N, where M is the number of marked state and N is the number of items in the dataset. We develop a robust quantum search algorithm based on Grover–Long algorithm with some uncertainty in the number of marked states. The proposed algorithm has the same query complexity ON as the Grover’s algorithm, and shows high tolerance of the uncertainty in the ratio M/N. In particular, for a database with an uncertainty in the ratio M±MN, our algorithm will find the target states with a success rate no less than 96%.

A quantum search algorithm for future spacecraft attitude determination

2011 ◽  
Vol 68 (7-8) ◽  
pp. 1208-1218 ◽  
Author(s):  
Jack Tsai ◽  
Fu-Yuen Hsiao ◽  
Yi-Ju Li ◽  
Jen-Fu Shen
Keyword(s):  
Attitude Determination ◽  
Search Algorithm ◽  
Spacecraft Attitude ◽  
Quantum Search ◽  
Quantum Search Algorithm

How significant are the known collision and element distinctness quantum algorithms?

2004 ◽  
Vol 4 (3) ◽  
pp. 201-206
Author(s):  
L. Grover ◽  
T. Rudolph
Keyword(s):  
Search Algorithm ◽  
Quantum Algorithms ◽  
Search Space ◽  
Space Complexity ◽  
Quantum Search ◽  
Quantum Search Algorithm ◽  
Time Space ◽  
Simple Quantum ◽  
Structured Problems ◽  
Better Than

Quantum search is a technique for searching $N$ possibilities for a desired target in $O(\sqrt{N})$ steps. It has been applied in the design of quantum algorithms for several structured problems. Many of these algorithms require significant amount of quantum hardware. In this paper we propose the criterion that an algorithm which requires $O(S)$ hardware should be considered significant if it produces a speedup of better than $O\left(\sqrt{S}\right)$ over a simple quantum search algorithm. This is because a speedup of $O\left(\sqrt{S}\right)$ can be trivially obtained by dividing the search space into $S$ separate parts and handing the problem to $S$ independent processors that do a quantum search (in this paper we drop all logarithmic factors when discussing time/space complexity). Known algorithms for collision and element distinctness exactly saturate the criterion.

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