Open Access Journal of Data Science and Artificial Intelligence (OAJDA)

ISSN: 2996-671X

Research Article

Exploring the Evolution of Quantum Computing: A Comparative Study of Grover’s Algorithm and Conventional Binary Search

Authors: Wheeler S , Putta N and Jakka VR

DOI: 10.23880/oajda-16000153

Abstract

The focus of this literature review is to examine the foundational principles and current advancements in the field of quantum computing, showcasing its potential to address challenges faced by traditional systems. This study concentrates on key concepts like superposition and entanglement, leading to an exploration of various quantum algorithms, such as Grover’s algorithm and Shor’s algorithm. By comparing Grover’s Search algorithm with binary search, the study aims to demonstrate quantum computing’s advantages in terms of efficiency and speed, especially for large datasets and unsorted databases. The comparison reveals the current state of quantum hardware and its limitations. Despite the challenges associated with hardware requirements, IBM has developed a quantum machine with a 456- qubit quantum processor, marking a milestone and showcasing rapid evolution in this field. Insights gained from this comparison include the potential for algorithms to handle scaled datasets, various applications in data science, and the capability to solve complex problems.

Keywords: History; Quantum Computer Architecture; Quantum Algorithms; Grover’s Algorithm; Binary Search; Performance Comparison; Time Complexity; Superposition; Entanglement; Quantum Gates; Data Science Applications; Quantum Mechanics; Quantum vs. Classical Computing; Qiskit

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