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The Physics Teacher

Grover’s Search Algorithm: An Approachable Application of Quantum Computing

Jed Brody, Grant-Christopher Worthington Sykes

Published Dec 30, 2024• 3 citations
Publisher
DOI
10.1119/5.0164714

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Abstract Solving combinatorial optimization problems represents a challenge for researchers, especially hard NP-complete problems that are commonly handled through heuristic methods providing approximate solutions. The emergence of quantum computing, which enables performing parallel computation, raises hope for solving such problems within a reasonable time frame. This paper proposes a quantum global optimization algorithm for solving combinatorial optimization problems with improved performance and runtime approaching Grover’s optimal time of quantum search. The algorithm determines the global optimum of the objective function defining the addressed problem using an enhanced application of Grover’s search by simultaneously exploring all comparison cases of possible solutions without requiring iterative operations, unlike previous approaches, which affect performance and runtime. The paper also introduces a version of the proposed algorithm for solving the knapsack problem, along with its execution results and a comparison with other competing algorithms.
Grover’s search algorithm is one of the most famous quantum algorithms, which enables search in unstructured dataspaces with a quadratic speedup over any known classical algorithm. This is one of the first algorithms to show quantum advantage over classical methods of computation. Besides its most anticipated application of brute force attack on symmetric key encryptions like AES, it is today being used in many modern applications as a subroutine. In this chapter, we describe the mathematical model of Grover’s quantum search algorithm, its behavior, and the theory of its circuit implementation. This chapter also discusses an exact variant of this algorithm and recent applications of Grover’s quantum search.
his study explores the application of quantum computing in solving complex mathematical problems through the utilization of Grover's Algorithm. Grover's Algorithm, renowned for its efficiency in unstructured search, has been adapted for various mathematical applications requiring rapid solution searches within large solution spaces. In this study, we implement Grover's Algorithm on a quantum computing platform to address a range of complex mathematical problems, including nonlinear equations and combinatorial optimization. Experimental results demonstrate that Grover's Algorithm significantly reduces computational time compared to classical methods, highlighting the immense potential of quantum computing in advanced mathematics. These findings pave the way for the development of more sophisticated quantum algorithms and their applications across science, engineering, and technology domains.