Hybrid Algorithms for Quantum Computing and Artificial Intelligence
Dr. V. Venkata Ramana, Dr. Pavithra M, Dr. Kriti Srivastava, Anvesh Perada
Indexed In: Google Scholar
Release Date: 07/12/2024 | Copyright:© 2024 | Pages: 458
DOI: 10.71443/9788197933646
ISBN10: 8197933642 | ISBN13: 9788197933646
The chapter Hybrid Algorithms for Quantum Computing and Artificial Intelligence delves into the groundbreaking potential of hybrid algorithms that synergize quantum and classical computing to solve complex problems across various domains. It introduces foundational concepts, focuses on the interplay between quantum mechanics and classical computation, and explores task distribution strategies and quantum-classical computation models. Highlighting the advantages of hybrid systems over standalone approaches, the chapter examines advancements such as variational quantum algorithms, quantum-assisted optimization, and hybrid neural networks. These innovations are contextualized with practical applications in supply chain management, energy distribution, and machine learning, showcasing their impact on efficiency, accuracy, and scalability. Real-world case studies illustrate the transformative capabilities of these algorithms, addressing challenges like noise and error correction in quantum systems. This chapter provides a comprehensive overview of hybrid architectures, emphasizing their role as a bridge to the future of computational science and innovation.
The scope of the chapter Hybrid Algorithms for Quantum Computing and Artificial Intelligence explores the integration of quantum and classical computing to solve complex challenges across various domains. It provides a foundational understanding of hybrid algorithms, emphasizing how quantum mechanics' phenomena like superposition and entanglement work with classical computational techniques. The chapter covers key topics such as task allocation strategies, quantum-classical computation models, and innovations like variational quantum algorithms and hybrid neural networks. Applications in supply chain management, energy optimization, and machine learning highlight the practical impact of these systems. It also addresses challenges like noise, error correction, and hardware limitations in implementing hybrid architectures. Serving as a vital resource, the chapter bridges theoretical knowledge with real-world applications, offering insights for students, researchers, and professionals working to harness hybrid computing in science, industry, and technology.
Dr. V. Venkata Ramana is working as a Professor in the Department of Computer Science Engineering at KSRM College of Engineering(A), Kadapa (Dist), A.P. He Completed his Master’s degree in Computer Science & Engineering from JNTUH, University, a Ph.D. degree from JNTUA University, Ananthapuramu. His areas of interest include Computer Networks, Mobile hoc networks, Bio-Inspired Networks, and other latest trends in technology. He has more than 21+ years of experience in teaching and research in the area of Computer science & Engineering. He has 7 book chapters and has attended 22 conferences. He also Published 30 + Journal papers, including 22 patents with 7 grant patents.
Dr. Pavithra M received her M.Sc. in Mathematics and Ph.D. in Mathematics from the University of Mysore, Mysuru, in the years 2008 and 2021, respectively. She qualified for the Karnataka State Eligibility Test (K-SET) for Assistant Professor in the year 2016. Her main research areas are graph theory, graph algorithms, and Degree-based Topological indices. She has 14 years of academic experience. She has published more than 15 research papers in these areas of research in journals of National and International repute. She has presented several research papers in these areas in National and International Conferences. Currently, Dr. Pavitha M. is working as an Assistant Professor at the Department of Studies in Mathematics, Karnataka State Open University, Mysuru.
Dr. Kriti Srivastava completed her Ph.D. in Computer Engineering in 2021. She is currently working as an Associate Professor in CSE( Data Science) at Dwarkadas J Sanghvi College of Engineering, Mumbai. She has 21 years of academic experience and has published more than 60 International Conference and Journal Papers. Her research interests are in Artificial Intelligence and Machine Learning.
Anvesh Perada is an accomplished author, Engineer, and innovator with a multidisciplinary background spanning Electrical engineering, Human Resources, and Operations management. He is the President (South India) of the Human Rights Council for India and holder of multiple patents in India, the UK, and Canada. Anvesh has made significant contributions to both academia and industry, particularly in artificial intelligence, quantum computing, and electric vehicles. With a B.Tech & M. Tech in Electrical & Electronics Engineering and an MBA in HR and Operations Management, Anvesh has applied a unique blend of technical insight and managerial expertise in roles ranging from Cloud engineer to HR professional.