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Quantum Computing Architecture and Hardware for Engineers - by Hiu Yung Wong (Hardcover)
About this item
Highlights
- About the Author: Hiu Yung Wong is an Associate Professor at San Jose State University.
- 371 Pages
- Technology, Electronics
Description
From the Back Cover
The purpose of this book is to teach quantum computing hardware from an engineer's perspective. Engineers play an important role in quantum computers. However, college and graduate engineering students usually do not have the required physics and mathematics training to understand how quantum computer hardware works. This book provides step-by-step guidance to connect engineers to the quantum world.
- Prepares readers with the essential mathematics and physics skills to understand and design quantum computers.
- Covers spin qubits and superconducting qubits in a unified framework.
- Uses language accessible to readers with varying backgrounds and a step-by-step approach.
- Includes simulation codes and superconducting quantum chip design examples.
- Discusses step-by-step the physics, mathematics, and their connection to microwave electronics based on how they fulfill the five DiVincenzo's criteria.
About the Author
Hiu Yung Wong is an Associate Professor at San Jose State University. He received his Ph.D. degree in Electrical Engineering and Computer Science from the University of California, Berkeley in 2006. From 2006 to 2009, he worked as a Technology Integration Engineer at Spansion. From 2009 to 2018, he was a TCAD Senior Staff Application Engineer at Synopsys.
He received the Industry Sponsored Research Award and ERFA RSCA Award in 2024, the AMDT Endowed Chair Award, the Curtis W. McGraw Research Award from ASEE Engineering Research Council in 2022, the NSF CAREER award and the Newnan Brothers Award for Faculty Excellence in 2021, and Synopsys Excellence Award in 2010. He is the author of the book, "Introduction to Quantum Computing: From a Layperson to a Programmer in 30 Steps". He is one of the founding faculties of the Master of Science in Quantum Technology at San Jose State University.
His research interests include the application of machine learning in simulation and manufacturing, cryogenic electronics, quantum computing, and wide bandgap device simulations. His works have produced 1 book, 1 book chapter, more than 120 papers, and 10 patents.