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Highlights in Science Engineering and Technology

Grover’s Algorithm – Implementations and Implications

Chenxi Guo

Published Mar 16, 2023• 12 citations
Publisher

Abstract

Ever since the realisation of the potential computational power of quantum-natured circuits, multiple quantum algorithms have been proposed, exploiting quantum superposition or quantum entanglement features to simulate quantum systems that classical computers cannot efficiently probe. The most notable among these strategies is Shor’s algorithm, which takes advantage of the quantum Fourier transform and has been shown capable of solving integer factorisation problems within polynomial time. This article’s focus is on one type of quantum algorithm based on amplitude amplification, namely Grover’s algorithm. This algorithm’s working principle is explained, and a discussion of its recent developments and possible direction of future reach is provided. In addition, implementations of Grover’s algorithm have been performed using the IBM Quantum Lab, followed by a reference to its connection to life sciences.

DOI
10.54097/hset.v38i.5997

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Ever since the realisation of the potential computational power of quantum-natured circuits, multiple quantum algorithms have been proposed, exploiting quantum superposition or quantum entanglement features to simulate quantum systems that classical computers cannot efficiently probe. The most notable among these strategies is Shor’s algorithm, which takes advantage of the quantum Fourier transform and has been shown capable of solving integer factorisation problems within polynomial time. This article’s focus is on one type of quantum algorithm based on amplitude amplification, namely Grover’s algorithm. This algorithm’s working principle is explained, and a discussion of its recent developments and possible direction of future reach is provided. In addition, implementations of Grover’s algorithm have been performed using the IBM Quantum Lab, followed by a reference to its connection to life sciences.
This paper presents the generalized implementation of the quantum circuit utilized in Shor’s algorithm, which was simulated using the quantum simulator offered by IBM. Shor’s Algorithm is a ground-breaking Quantum Algorithm that works on Integer Factorization; for a classical computer, the following task would require an exponential amount of time, whereas a Quantum Computer running Shor’s Algorithm would only require Polynomial-time. Using the principles of Quantum Superposition and Quantum Entanglement, the algorithm demonstrates the potential of quantum computing to solve complex mathematical problems efficiently. Experimental results show the effectiveness of the implemented algorithm in Integer Factorization and discrete logarithm, disturbing the safety of major encryption algorithms. This paper contributes to advancing the understanding and practical application of quantum algorithms in real-world scenarios.
This review paper provides an in-depth exploration of quantum computing and the algorithms that drive its potential. It begins by introducing quantum computers and explores various types of quantum computers, focusing on the most prominent architectures. This paper also explains the concept of qubits, highlighting their unique properties such as superposition and entanglement, which differentiate quantum systems from classical computing. It discusses the specific properties of quantum computers that make them particularly suited to solving certain classes of problems, such as optimization, cryptography, and simulation. Additionally, the paper provides a detailed overview of key quantum algorithms, including Shor’s algorithm for integer factorization, Grover’s algorithm for unstructured search, and the use of quantum simulation in modelling complex physical systems. Through this review, we aim to showcase the evolving landscape of quantum computing, its capabilities, and the algorithms driving its future impact across various fields.
For decades, classical computers have been governed by predictable rules. But as we approach the physical limits of computation, a new paradigm is emerging. Quantum computing operates on the strange and powerful laws of quantum mechanics—superposition, entanglement, and interference—to tackle problems far beyond the reach of any classical machine. The true potential of this field was unlocked by two landmark discoveries: Shor’s algorithm, a revolutionary method for integer factorization that threatens to upend modern cryptography, and Grover’s algorithm, a versatile tool that offers a quadratic speedup for unstructured search problems. This paper serves as a guide to these foundational algorithms, detailing their inner workings and their profound impact. We also explore post-quantum cryptography, hybrid frameworks, and quantum machine learning—illustrating the evolving role of quantum algorithms in shaping the future of science and technology.
Quantum computing introduces an efficient way for unfolding complex problems on computing systems. It uses concept of superposition and entanglement, & hence supports intrinsic parallelism for obtaining the speedup in context of time over classical computing. Quantum algorithms can be efficiently implemented over quantum computing system. Most popular quantum algorithms like Grover's and Shor's provide a great foundation to specifically design the algorithms. These algorithms work on improving the lower runtime bounds of classical algorithms. Grover's algorithm exhibits a quadratic polynomial speedup while searching an element among `N' elements unstructured database. The algorithmic strategy can be applied over various computer science related applications and some important are being considered in this article i.e. pattern matching, data mining and machine learning. This article explores quantum fundamentals; history based evolution followed by Grover's search algorithm in detail with cascading advantages, limitations & applications and also finally concludes with the significance of quantum computing & quantum algorithmic domains.
Quantum computing, based on the fundamental principles of quantum mechanics, has become a breakthrough that has the potential to revolutionize computing. At the forefront of this quantum revolution are quantum algorithms that use the origin of qubits to solve computational problems much faster than classical algorithms. This article provides a review of quantum algorithms to introduce their principles, examine famous examples such as the Grover and Shor algorithms, and delve into their applications, including quantum machine learning. Exploring the fundamentals of quantum computing begins with an overview that highlights the unique features of quantum computing compared to classical computing. We then examine several different algorithmic paradigms to highlight the unique advantages that quantum parallelism and interference bring to computing. The best knowledge of quantum algorithms focuses on Grover's blind search, Shor's efficient factorization algorithm, and the quantum phase approach for solving quantum chemistry and eigenvalue problems. As well as celebrating the achievements of quantum algorithms, this research also looks at the challenges and limitations that hinder their widespread use. Topics such as decoherence, error correction, and finding errors in quantum computing are discussed in the context of overcoming obstacles to the use of practical quantum algorithms. In addition, the latest developments are clarified by showing the successes of the experiments and their implications for the future. As we stand at the forefront of a new era in computing, this article not only provides a snapshot of the current state of quantum algorithms but also speculates on future directions. The potential applications of quantum algorithms in many fields and the ongoing quest to overcome current limitations offer exciting opportunities for further research. This research aims to contribute to the ongoing debate about quantum algorithms, gaining a deeper understanding of their impact on the future of computing.
Quantum Fourier transform (QFT) plays an eminent role in quantum computation.It creates a superposition of different quantum states, allowing simultaneous calculation, which would take many steps were the same program implemented on a classical computer.The computational speed of a quantum computer is thus boosted dramatically.In this article, we explain the application of QFT in Shor's algorithm, which was proposed by Peter Shor to factor large integers on quantum computers.Specifically, the principle and design of quantum Fourier transform are explained.We stress the subtle distinction between QFT and its inverse.Since former articles did not emphasize it, we hope it could be a supplement to former articles.Our next work is to verify the existing articles on executing Shor's algorithm by conducting two experiments on IBMQ of factoring N = 15 in two ways (a = 7 and a = 11).We find that the effect of quantum entanglement might be crucial to the speed boost of factoring large integers in Shor's algorithm.