Programming Quantum Computers: Essential Algorithms and Code Samples (1)
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- Synopsis
- Quantum computers are poised to kick-start a new computing revolution—and you can join in right away. If you’re in software engineering, computer graphics, data science, or just an intrigued computerphile, this book provides a hands-on programmer’s guide to understanding quantum computing. Rather than labor through math and theory, you’ll work directly with examples that demonstrate this technology’s unique capabilities.Quantum computing specialists Eric Johnston, Nic Harrigan, and Mercedes Gimeno-Segovia show you how to build the skills, tools, and intuition required to write quantum programs at the center of applications. You’ll understand what quantum computers can do and learn how to identify the types of problems they can solve.This book includes three multichapter sections:Programming for a QPU—Explore core concepts for programming quantum processing units, including how to describe and manipulate qubits and how to perform quantum teleportation.QPU Primitives—Learn algorithmic primitives and techniques, including amplitude amplification, the Quantum Fourier Transform, and phase estimation.QPU Applications—Investigate how QPU primitives are used to build existing applications, including quantum search techniques and Shor’s factoring algorithm.
- Copyright:
- 2019
Book Details
- Book Quality:
- Publisher Quality
- Book Size:
- 336 Pages
- ISBN-13:
- 9781492039631
- Related ISBNs:
- 9781492039655, 9781492039686, 9781492039648
- Publisher:
- O'Reilly Media
- Date of Addition:
- 02/06/25
- Copyrighted By:
- Eric R. Johnston, Nic Harrigan, Mercedes Gimeno-Segovia
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Computers and Internet, Mathematics and Statistics
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
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- by Eric R. Johnston
- by Nic Harrigan
- by Mercedes Gimeno-Segovia
- in Nonfiction
- in Computers and Internet
- in Mathematics and Statistics