Quantum Computing: A Shift from Bits to Qubits

Name: Quantum Computing: A Shift from Bits to Qubits
Author: Rajiv Pandey
ISBN: 9789811995293

Rajiv Pandey

Language: English

Published by Springer, Springer Nature Singapore Mär 2023, 2023

981199529X / 9789811995293

Series: Book 536 of 538 - Studies in Computational Intelligence

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This item is printed on demand - Print on Demand Titel. Neuware -The edited book is a consolidated handbook on quantum computing that covers quantum basic science and mathematics to advanced concepts and applications of quantum computing and quantum machine learning applied to diverse domains. The book includes dedicated chapters on introduction to quantum computing, its practical applications, the working behind quantum systems, quantum algorithms, quantum communications, and quantum cryptography. Each challenge that can be addressed with quantum technologies is further discussed from theoretical and practical perspectives. The book is divided into five parts: Part I: Scientific Theory for Quantum, Part II: Quantum Computing: Building Concepts, Part III: Quantum Algorithms- Theory & Applications, Part IV: Quantum Simulation Tools & Demonstrations, and Part V: Future Direction and Applications.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 504 pp. Englisch.

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Title: Quantum Computing: A Shift from Bits to Qubits
Author: Rajiv Pandey
Publisher: Springer, Springer Nature Singapore Mär 2023
Publication year: 2023
Condition: Neu
Binding: Buch
Language: English
ISBN 10: 981199529X
ISBN 13: 9789811995293
Item weight: 1,008 grams
Dimensions: 241x160x31 mm
Series: Book 536 of 538: Studies in Computational Intelligence

About the Author

Dr. Rajiv Pandey Senior Member IEEE is a Faculty at Amity Institute of Information Technology, Amity University, Uttar Pradesh, Lucknow Campus India. He has edited various volumes on AI/ML in Edge Computing and Semantic IoT, published by Springer and Elsevier. He possesses a diverse background experience of around 40 years to include 15 years of Industry and 20 years of academics. His research interests include contemporary technologies as Quantum computing, Blockchain and cryptocurrencies, Semantic Web Provenance, Cloud and Big Data, and Data Analytics. He has published more than 50 research papers in Scopus, and other science indexed journals of repute. He has been Session chairs, technical committee member for various IEEE and Elsevier conferences. He has been awarded by DST, Government of India during IISF and is on technical committees of various government and private universities. He is intellectually involved in supervising doctorate research scholars Three scholars have been awarded Ph.D. and three are on the verge of submitting the final thesis. He is also an active contributor in professional bodies like IEEE, IET, and Lucknow Management Association. He has filed patents and received Grants form AICTE India.

Dr. Nidhi Srivastava is currently working as Assistant professor at Amity Institute of Information Technology, Amity University, Uttar Pradesh, Lucknow Campus, India. She has more than 15 years of teaching experience. Dr. Nidhi has a rich and diverse experience in academia. Her research interests include Human–Computer Interaction, Cloud Computing, Semantic Web, and Artificial Intelligence. She has more than 30 publications in various international/national journals and conferences. She has also edited a book on Semantic Web published in book series Studies in Computational Intelligence, Springer. She is Reviewer and Editorial Board Member of several international journals. She has been nominated as Member of Technical Committee and Organizing Committee of many international/national conferences. She is also Member of many international and national bodies like CSI, IAENG, IDES, SDIWC, etc.

Dr. Neeraj Kumar Singh is an Associate Professor in computer science at INPT-ENSEEIHT and member of the ACADIE team at IRIT. Before joining INPT, Dr. Singh worked as a research fellow and team leader at the Centre for Software Certification (McSCert), McMaster University, Canada. He worked as a research associate in the Department of Computer Science at University of York, UK. He also worked as a research scientist at the INRIA Nancy Grand Est Centre, France, where he has received his Ph.D. in computer science. He leads his research in the area of theory and practice of rigorous software engineering and formal methods to design and implementation of safe, secure and dependable critical systems. He has authored/edited two books and one conference proceeding. He published more than 80+ peer-reviewed researcharticles in well-known journals, books and international conferences. He has been involved in many scientific activities. He is also involved in several research projects on formal methods and system engineering as project leader and as scientific coordinator.

Dr. Kanishka Tyagi is a senior machine learning scientist at Aptiv advances engineering center, California. He received his Bachelor's Degree in Electrical Engineering in 2008 from Pantnagar, India. Later he worked as a Research Associate at the Department of Electrical Engineering, Indian Institute of Technology, Kanpur, with Dr. P. K. Kalra. He received his Master’s and Doctoral degree with Dr. Michael Manry in the Department of Electrical Engineering at The University of Texas at Arlington in 2012 and 2017. Prior to Aptiv, he worked at Siemens research, interned in machine learning groups at The MathWorks and Google Research. He has worked as a visiting researcher at Ajou University and Seoul NationalUniversity. His research interests are radar machine learning, neural networks and hardware machine learning. He received the 2007 and 2011 IEEE CIS Outstanding Student Paper Travel Grant Award and 2013 IEEE CIS Walter Karplus Summer Research Grant award. Dr. Tyagi has taught four undergraduate/graduate courses on Big Data, soft computing and machine learning. Dr. Tyagi is a IEEE senior member, member of IEEE-CIS industrial-academic committee and IEEE standards committee on Explainable AI. He currently serves as an associate editor for IEEE Transaction on Neural Network and Learning Systems and IEEE Transactions on Artificial Intelligence. Dr. Tyagi has published over 30+ papers and filed 17 U.S. patents and trade secrets.

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Quantum Computing: A Shift from Bits to Qubits

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