Quantum computing is a rapidly emerging technology that harnesses the laws of quantum mechanics to solve problems too complex for classical computers. It is a multidisciplinary field comprising aspects of computer science, physics, and mathematics that utilizes quantum mechanics to solve complex problems faster than classical computers. It is a computational technology that uses the principles of quantum mechanics, such as entanglement, superposition, and interference to process, store, and manipulate large amounts of data and perform complex calculations for conventional computing systems and supercomputers cannot fathom.
Quantum Computing: Research, Applications, and Advances provides a comprehensive overview of the foundational principles of quantum mechanics that underpin quantum computing. It explains such concepts as superposition, entanglement, and quantum gates to demystify the esoteric nature of quantum phenomena. It delves into the current state of quantum computing research, presenting an insightful analysis of the latest breakthroughs and technological advancements. From the race to achieve quantum supremacy to the development of scalable quantum hardware, the book offers a detailed exploration of the key players, their methodologies, and the challenges they face in pushing the boundaries of quantum computing capabilities. It explores the practical applications of quantum computing across various domains. From cryptography to optimization problems and drug discovery, the book also illustrates how quantum algorithms have the potential to outperform classical counterparts to open doors to new possibilities where traditional computing falls short. The book integrates theoretical concepts and practical applications. The highlights include the following:
- Quantum computing in machine learning
- Harnessing quantum computing for predictive analysis
- Quantum-powered financial fraud detection
- Enhancing deep learning with quantum computing
- Quantum computing in medical imaging
Table of Contents:
1. Quantum Computing in Artificial Intelligence 2. Quantum Computing Transforming Machine Learning: An Overview 3. Quantum Computing in Machine Learning 4. Harnessing Quantum Computing for Predictive Analysis: Understanding the Social Media Impact on Stock Market Investment 5. Quantum-Powered Fraud Detection: Revolutionizing Financial Security 6. Quantum Computing in Healthcare 7. Quantum Computing in Healthcare: Applications and Challenges 8. Enhancing Deep Learning with Quantum Computing: Its Challenges, Opportunities, and Applications 9. Design and Optimization of Quantum Arithmetic Circuits for Next-Generation Quantum Systems 10. Quantum Key Distribution: Visualizing the Foundations of Future-Proof Secure Communication 11. Challenges and Opportunities of Quantum Computing in Medical Imaging 12. Quantum Computing and Industry Transformation 13. Next-Generation Quantum Algorithms: Trends, Techniques, and Applications 14. Applications of Deep Learning Technology for Mobile and Quantum Computing 15. Effective Quantum, Artificial Intelligence (AI), and Cloud Implementation 16. Quantum Supremacy and Its Applications
About the Author :
Dr. Arun Sekar Rajasekaran is an associate professor and associate head for the Department of Electronics and Communication Engineering at SR University, Warangal, Telangana, India.
Dr. Suganyadevi S. is an Assistant Professor in the Department of ECE at KPR Institute of Engineering and Technology, Tamilnadu, India.
Prof. Dr. Fadi Al-Turjman is the associate dean for research and the founding director of the International Research Center for AI and IoT at Near East University, Nicosia, Cyprus.
