Quantum Computing, Research, Applications, and Advances, Rajasekaran A.S., Suganyadevi S., 2026

Quantum Computing, Research, Applications, and Advances, Rajasekaran A.S., Suganyadevi S., 2026.

   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 as they push 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.




Portfolio Optimization Using QAOA.
Combinatorial optimization issues may be resolved using the variational hybrid quantum–classical technique known as the QAOA. Portfolio optimization, where the objective is to choose the best subset of assets to maximize returns while minimizing risk within limitations, has been experimentally implemented.

To solve tiny issue cases, Egger et al. (2020, IBM) developed a portfolio selection process based on QAOA using an NISQ device. For small-scale cases, this experiment demonstrated how QAOA circuits may approximate solutions with performance competitive to conventional heuristics, highlighting the practical viability of quantum optimization techniques for finance.

Contents.
Editors.
Contributors.
Preface.
Acknowledgments.
Chapter 1 Quantum Computing in Artificial Intelligence.
Chapter 2 Quantum Computing Transforming Machine Learning: An Overview.
Chapter 3 Quantum Computing in Machine Learning.
Chapter 4 Harnessing Quantum Computing for Predictive Analysis: Understanding the Social Media Impact on Stock Market Investment.
Chapter 5 Quantum-Powered Fraud Detection: Revolutionizing Financial Security.
Chapter 6 Quantum Computing in Healthcare.
Chapter 7 Quantum Computing in Healthcare: Applications and Challenges.
Chapter 8 Enhancing Deep Learning with Quantum Computing, Its Challenges, Opportunities, and Applications.
Chapter 9 Design and Optimization of Quantum Arithmetic Circuits for Next-Generation Quantum Systems.
Chapter 10 Quantum Key Distribution: Visualizing the Foundations of Future-Proof Secure Communication.
Chapter 11 Challenges and Opportunities of Quantum Computing in Medical Imaging.
Chapter 12 Quantum Computing and Industry Transformation.
Chapter 13 Next-Generation Quantum Algorithms: Trends, Techniques, and Applications.
Chapter 14 Applications of Deep Learning Technology for Mobile and Quantum Computing.
Chapter 15 Effective Quantum, Artificial Intelligence (AI), and Cloud Implementation.
Chapter 16 Quantum Supremacy and Its Applications.
Index.



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Теги: учебник по информатике :: информатика :: компьютеры :: Rajasekaran :: Suganyadevi