Quantum Computing - by Andrew Glassner (Paperback)

About the Book

"An introduction to quantum computing that uses high school-level mathematics to explain the unusual behaviors of quantum computers, then expands to the formulas and techniques used in those computers' unique programs. Covers practical applications of quantum computing and guides readers to create and run their own algorithms using freely available online simulators"-- Provided by publisher.

Book Synopsis

A friendly introduction to quantum programming.

What if you had a computer that could process billions of different inputs at the same time?

Quantum computing is a radically new way to think about algorithms and data. It can feel mysterious or technically challenging, but it doesn't have to be. If you want to understand how quantum computers work--and how to program them--this friendly, self-contained guide is for you.

This approachable yet rigorous book walks you step-by-step through quantum computing fundamentals, such as superposition, quantum gates, interference, entanglement, and measurement, then teaches you how to write real quantum programs.

Along the way, you'll:

• Understand how to store and transform quantum information
• Grasp the surprising process of quantum measurement
• Explore Simon's, Grover's, and Shor's algorithms
• Write and run your own quantum code using free simulators and live hardware

Author Andrew Glassner is known for turning complex topics into accessible and enjoyable learning experiences. In this book, he brings visual thinking, clarity, context, and precision to the strange and fascinating world of quantum programming. All the ideas and math are built up slowly so you'll master every step.

Whether you're a programmer, student, educator, scientist, poet, or anyone else who loves new ideas that stretch your mind, this is the guide that will take you from "What is a qubit?" to writing and running working quantum algorithms with curiosity, creativity, and confidence.

About the Author

Andrew Glassner, PhD, is a principal research scientist at FX, where he uses deep learning to help artists produce visual effects for film and TV. He was technical papers chair for SIGGRAPH '94, founding editor of the Journal of Computer Graphics Techniques, and editor in chief of ACM Transactions on Graphics. His prior books include Deep Learning: A Visual Approach (No Starch Press), the Graphics Gems series, and the textbook Principles of Digital Image Synthesis. In his free time, he paints, writes novels, and plays jazz piano.