Quantum Algorithms of Bio-molecular Solutions for the Clique Problem on a Quantum Computer

TL;DR

This paper demonstrates how DNA-based algorithms for the clique problem can be implemented on a quantum computer using various quantum gates, leading to faster target state labeling and more efficient problem solving.

Contribution

It introduces a quantum implementation of the DNA-based clique problem algorithm, optimizing the oracle work and improving solution speed on quantum computers.

Findings

Quantum implementation uses Hadamard, NOT, CNOT, CCNOT gates, and Grover's operators.

Faster target state labeling reduces overall problem-solving time.

Quantum approach achieves more efficient clique problem solutions.

Abstract

In this paper, it is demonstrated that the DNA-based algorithm [Ho et al. 2005] for solving an instance of the clique problem to any a graph G = (V, E) with n vertices and p edges and its complementary graph G1 = (V, E1) with n vertices and m = (((n*(n-1))/2)-p) edges can be implemented by Hadamard gates, NOT gates, CNOT gates, CCNOT gates, Grover's operators, and quantum measurements on a quantum computer. It is also demonstrated that if Grovers algorithm is employed to accomplish the readout step in the DNA-based algorithm, the quantum implementation of the DNA-based algorithm is equivalent to the oracle work (in the language of Grover's algorithm), that is, the target state labeling preceding Grover,s searching steps. It is shown that one oracle work can be completed with O((2 * n) * (n + 1) * (n + 2) / 3) NOT gates, one CNOT gate and O((4 * m) + (((2 * n) * (n + 1) * (n + 14)) / 6)) CCNOT gates. This is to say that for the quantum implementation of the DNA-based algorithm [Ho et al. 2005] a faster labeling of the target state is attained, which also implies a speedy solution to an instance of the clique problem.