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De Gruyter eBooks

Chapter 13 Introduction to quantum computing and its revolution in industry and society

Sarita, Riya Sapra, Yogita Yashveer Raghav

Published Dec 16, 2024• 2 citations
Publisher

Abstract

Quantum computing is nowadays a very popular topic in terms of technology, enabling individuals to solve various types of computational problems. Quantum computing is a multidisciplinary area consisting of Information Technology, mathematics, and physics that uses quantum theory/mechanism. Classical computer systems use the binary number system (0 or 1), whereas quantum computers use quantum bits that represent both 0 and 1 together. Quantum computing is used in solving optimization problems. Quantum computing improves machine learning algorithms by efficiently analyzing complex data. Quantum computers can improve AI models by training them quickly. Quantum computing has an impact in the sectors of healthcare, finance, security, etc., and each has its own applications.

DOI
10.1515/9783111354842-013

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Quantum computing is nowadays a very popular topic in terms of technology, enabling individuals to solve various types of computational problems. Quantum computing is a multidisciplinary area consisting of Information Technology, mathematics, and physics that uses quantum theory/mechanism. Classical computer systems use the binary number system (0 or 1), whereas quantum computers use quantum bits that represent both 0 and 1 together. Quantum computing is used in solving optimization problems. Quantum computing improves machine learning algorithms by efficiently analyzing complex data. Quantum computers can improve AI models by training them quickly. Quantum computing has an impact in the sectors of healthcare, finance, security, etc., and each has its own applications.
Quantum computing is an emerging form of computing that uses the rules of quantum physics to process information in ways that are far different from how computers do it now. Quantum computing uses quantum bits, or qubits, which can exist in superpositions of states and get entangled with each other, which is different from classical computing, which uses a bit that represents binary values (0 or 1). These characteristics allow quantum devices to execute parallel computations, enabling significant speedups for specific categories of problems considered intractable for classical machines. This chapter gives a thorough introduction to quantum computing, starting with a historical overview of its foundations in quantum physics and significant theoretical advancements. It analyzes fundamental ideas including superposition, entanglement, quantum interference, and the no-cloning theorem, explaining how these elements distinguish quantum computation from traditional approaches. The advancement of quantum hardware is examined through several architectures, trapped ions, superconducting circuits, photonics, and topological qubits, together with software frameworks like Qiskit, Cirq, and PennyLane, which support algorithm development and simulation. The chapter examines fundamental quantum algorithms, such as Grover’s algorithm for database search, Shor’s algorithm for integer factorization, and hybrid variational methods designed for noisy intermediate-scale quantum devices. The practical applications in domains including as encryption, optimization, machine learning, chemistry, and finance emphasize the real-world significance of quantum technology. Challenges like decoherence, noise, scalability, and algorithmic maturity are rigorously analyzed, followed by an anticipated discourse on future trajectories including fault-tolerant architectures, quantum networking, and the development of quantum cloud services. This chapter presents a fundamental introduction for students, researchers, and practitioners seeking to comprehend the essential principles, functionalities, and possibilities of quantum computing in the post–Moore’s law period.
Quantum computing is a rapidly evolving field with a wide range of applications in diverse industries.Hybrid quantum computing combines classical and quantum computing to solve complex problems, quantum machine learning is a subset of machine learning that leverages quantum computing for optimization, and quantum embeddings use quantum algorithms to process high dimensional data.Quantum computers have the potential to revoltionize finance, industry, production, drug research, and even consumer-facing services.With quantum computing's ability to handle massive amounts of data and perform complex calculations at incredible speeds, it holds great promise for addressing some of the world's most pressing problems in these areas.
Quantum Computing The twenty-first century has witnessed remarkable advancements in computing technologies, transforming every aspect of modern society. As conventional computing systems approach their physical and computational limits, the search for new paradigms capable of solving increasingly complex problems has led to the emergence of Quantum Computing. By harnessing the principles of quantum mechanics, quantum computing represents a revolutionary approach that has the potential to redefine computation, communication, and information processing on an unprecedented scale. Quantum Computing is designed to provide readers with a comprehensive understanding of the concepts, principles, technologies, and applications that form the foundation of this rapidly evolving field. This book aims to bridge the gap between theoretical quantum mechanics and practical computational applications, enabling students, researchers, academicians, and professionals to explore the transformative potential of quantum technologies. The chapters in this book cover a broad spectrum of topics, including the fundamentals of quantum mechanics, quantum bits (qubits), quantum gates, superposition, entanglement, quantum circuits, quantum algorithms, quantum cryptography, quantum communication, and quantum error correction. The book also explores the architecture of quantum computers and examines the challenges involved in building scalable and fault-tolerant quantum systems. As industries increasingly seek innovative solutions to complex computational problems, quantum computing is emerging as a promising technology with applications in cryptography, artificial intelligence, machine learning, optimization, financial modeling, healthcare, pharmaceutical research, materials science, logistics, and climate modeling. The ability of quantum computers to process vast amounts of information simultaneously offers opportunities that were previously beyond the reach of classical computing systems. Special attention has been given to contemporary developments in quantum technologies, including quantum supremacy, hybrid quantum-classical computing, cloud-based quantum platforms, and the growing role of quantum computing in scientific discovery and industrial innovation. The book also discusses ethical, security, and societal implications associated with the advancement of quantum technologies. The primary objective of this book is to equip readers with both foundational knowledge and practical insights into the field of quantum computing. Through a balanced presentation of theory, applications, case studies, and emerging research trends, the book seeks to inspire curiosity, innovation, and further exploration in this transformative domain. We extend our sincere gratitude to the authors, reviewers, researchers, academicians, and industry experts whose valuable contributions have enriched the quality and relevance of this publication. Their dedication and expertise have helped create a resource that reflects the latest developments and future possibilities of quantum computing. We hope that Quantum Computing will serve as a valuable guide for students, educators, researchers, and technology professionals seeking to understand the next frontier of computational science. May this book inspire new ideas, foster innovation, and contribute to the advancement of knowledge in one of the most exciting technological revolutions of our time. Mr. M. Rajeshkumar Dr. R. Mariappan Mr. E.Janakiraman,
Quantum computing is a potential technological revolution that will transform the entire field of information processing. However, quantum computing like classical bits in classical computers is operated using quantum bits principle physics based on quantum mechanics. Quantum computing explores many solution spaces simultaneously because of a fundamental difference from the classical computation paradigms, leading to the possibility of exponential speed-up on some computational plant tasks. This paper discusses quantum computing with essential concepts like quantum superposition, entanglement, and applications such as cryptography, optimization, and drug discovery and machine learning. Quantum computing will enable numerous groundbreaking discoveries that were previously unattainable and will bequeath a lasting legacy in the digital innovation era. Quantum computing is an information processing technique that harnesses the laws of quantum mechanics to conduct calculations far faster circumvented by traditional digital computers. Digital computers utilize bits, which may take one of two forms: 0 or 1. This superposition of quantum superposition and entanglement yielded qubits unique qualities that can’t be expected in classical systems. Indeed, superposition enables qubits to take numerous forms simultaneously, while entanglement enables qubits to be connected such their properties are connected. In cryptography, quantum computers can decrypt existing cryptographic keys or develop new, more secure quantum encryption using qubits. Quantum computers can dramatically accelerate materials science and drug design by allowing scientists to simulate how molecules interact more accurately. In conclusion, quantum computing represents a unique information processing change and has a future impact on science, technology, and society.
The book explores the latest quantum computing research focusing on problems and challenges in the areas of data transmission technology, computer algorithms, artificial intelligence-based devices, computer technology, and their solutions. Future quantum machines will exponentially boost computing power, creating new opportunities for improving cybersecurity. Both classical and quantum-based cyberattacks can be proactively identified and stopped by quantum-based cybersecurity before they harm. Complex math-based problems that support several encryption standards could be quickly solved by using quantum machine learning. This comprehensive book examines how quantum machine learning and quantum computing are reshaping cybersecurity, addressing emerging challenges. It includes in-depth illustrations of real-world scenarios and actionable strategies for integrating quantum-based solutions into existing cybersecurity frameworks. A range of topics are examined, including quantum-secure encryption techniques, quantum key distribution, and the impact of quantum computing algorithms. Additionally, it talks about machine learning models and how to use machine learning to solve problems. Through its in-depth analysis and innovative ideas, each chapter provides a compilation of research on cutting-edge quantum computer techniques, like blockchain, quantum machine learning, and cybersecurity. Audience This book serves as a ready reference for researchers and professionals working in the area of quantum computing models in communications, machine learning techniques, IoT-enabled technologies, and various application industries such as finance, healthcare, transportation and utilities.
Quantum computing is a novel kind of computation that solves very complicated problems rapidly by applying concepts from basic physics. Concepts like quantum mechanical computing and quantum algorithms are included in the field of quantum computing study. Researchers have imagined quantum computing as a revolutionary idea among emerging technologies in terms of concepts, methods, and techniques. These are cross-pollinated. Hence, quantum computing becomes more and more multidisciplinary. Quantum computing leverages quantum mechanical phenomena like superposition and quantum interference to deal with some kinds of problems more precisely than conventional computing. Because of its unique characteristics, which set it apart from conventional computers in terms of functionality and operation, quantum computing has grown in popularity. There are possibilities of creating hybrid models, namely approaches for large-scale mixed-integer programming issues, that effectively combine the strengths of quality control techniques with deterministic algorithms to handle combinatorial challenges.