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Dancing with Qubits

Dancing with Qubits

By : Robert S. Sutor
5 (24)
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Dancing with Qubits

Dancing with Qubits

5 (24)
By: Robert S. Sutor

Overview of this book

Dancing with Qubits, Second Edition, is a comprehensive quantum computing textbook that starts with an overview of why quantum computing is so different from classical computing and describes several industry use cases where it can have a major impact. A full description of classical computing and the mathematical underpinnings of quantum computing follows, helping you better understand concepts such as superposition, entanglement, and interference. Next up are circuits and algorithms, both basic and sophisticated, as well as a survey of the physics and engineering ideas behind how quantum computing hardware is built. Finally, the book looks to the future and gives you guidance on understanding how further developments may affect you. This new edition is updated throughout with more than 100 new exercises and includes new chapters on NISQ algorithms and quantum machine learning. Understanding quantum computing requires a lot of math, and this book doesn't shy away from the necessary math concepts you'll need. Each topic is explained thoroughly and with helpful examples, leaving you with a solid foundation of knowledge in quantum computing that will help you pursue and leverage quantum-led technologies.
Table of Contents (26 chapters)
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1
I Foundations
8
II Quantum Computing
14
III Advanced Topics
18
Afterword
22
Other Books You May Enjoy
23
References
24
Index
Appendices

About the reviewers

Gerhard Hellstern (Prof., Dr. rer. nat, graduate physicist, *1971) is a full professor at the Faculty of Economics at the Baden-Württemberg Cooperative State University in Stuttgart. From 1990–1995, he studied physics at the University of Tübingen and the State University of New York at Stony Brook; in 1998, he graduated as Dr. rer. nat. From 1998 to 2018, he was employed by several commercial banks and then for 17 years at Deutsche Bundesbank. There, he was in charge of the banking audits division for many years.

Gerhard Hellstern has been involved in the application of data science methods (data analytics as well as machine and deep learning) in finance for many years. These methods also include quantum computing as well as quantum machine learning based on it. He is a Qiskit advocate at IBM and a member of the research network Quantum Computing of the Fraunhofer Gesellschaft, Germany. His current research focuses on applications of quantum computing and quantum machine learning in the financial sector and beyond and he has published several papers in this domain.

Prateek Jain is an inquisitive person with a lifelong passion for science. He is currently focusing and researching quantum computing technologies and algorithms, focusing on the intersection of quantum computing and AI. He leads Quantum AI research at Fractal Analytics. He has over 5 years’ research experience in quantum computing and technologies and 18 years' experience in machine learning and artificial intelligence. He possesses a Master’s in quantum computing technologies from the Technical University of Madrid and a Master's in innovation and entrepreneurship from HEC Paris. He is also an IBM Quantum advocate and educator and his research interests include quantum computing, quantum machine learning, machine learning, and AI because it is fascinating to ponder the greatest questions of our age and catch a glimpse of how the world would look in the future.

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