Introduction to Quantum Computing: From a Layperson to a Programmer in 30 Steps - Tapa blanda

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Hiu Yung Wong is an Associate Professor and Silicon Valley AMDT Endowed Chair in Electrical Engineering, at San Jose State University (SJSU). He received his Ph.D. degree in EECS from UC 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 Engineer at Synopsys.

Given the important role of electrical engineers in the quantum computing industry, he created a new master's specialization in quantum computing at SJSU. He is also one of the founding faculties of the MS degree program in Quantum Technology at SJSU, sponsored by NSF. Based on his quantum computing teaching experience to electrical engineers, he authored the book "Introduction to Quantum Computing: From a Layperson to a Programmer in 30 Steps" with teaching videos available on Youtube (@quantum_computing). He also created a class on Quantum Computing Architectures (available on YouTube) and Cryogenic Nanoelectronics to train the next generation of electrical engineers in quantum computing. He is an organizer and speaker in the Real-World Quantum Computing Workshop with Lawrence Livermore National Lab to orient engineering students to work on superconducting quantum computers.

Dr. Wong has given numerous tutorials to promote quantum computing. He was invited to give a tutorial at the ISQED conference and IEEE Quantum Week 2023, and a public seminar for FormFactor, Inc. in 2022 (> 300 attendees). He has also given quantum computing talks in companies such as Fujitsu Research of America, eBay Inc, and Synopsys Inc. and study groups such as Zen4Quantum and Washington DC Quantum Computing Meetup. He gives yearly quantum computing workshops for socially-disadvantaged high school students sponsored by NSF funding.

He received the McGraw Research Award from ASEE in 2022, the NSF CAREER award and the Newnan Brothers Award in 2021, and Synopsys Excellence Award in 2010.

His education and research works have produced 1 book, 1 book chapter, more than 100 papers, and 10 issued patents.

De la contraportada

This textbook introduces quantum computing to readers who do not have much background in linear algebra based on the self-study experience of the author as an engineer. The author targets undergraduate and master students who are willing to spend about 60 -90 hours seriously learning quantum computing. This book is also suitable for self-study and teaching videos for each chapter and more than 200 exercises with answers are provided. Readers will be able to write their program to simulate quantum computing algorithms and run on real quantum computers on IBM-Q. Moreover, unlike books that only give superficial, "hand-waving" explanations, this book uses exact formalism so readers can continue to pursue more advanced topics based on what they learn from this book.

• Uses narrative to start each section with analogies that help students to grasp the critical concept quickly;
• Uses numerical substitutions, accompanied by Python programming and IBM-Q quantum computer programming, as examples in teaching all critical concepts;
• Teaching videos and more than 200 exercises with answers are provided.