Learn Quantum Computing with Python and Q#: A hands-on approach

Sarah Kaiser

ISBN 10: 1617296139 / ISBN 13: 9781617296130

Published by Manning Publications, 2021

About this Item

2021. 1st Edition. Paperback. . . . . . Books ship from the US and Ireland.

Seller Inventory # V9781617296130

Bibliographic Details

• Title: Learn Quantum Computing with Python and Q#: A hands-on approach
• Publisher: Manning Publications
• Publication Date: 2021
• Language: English
• ISBN 10: 1617296139
• ISBN 13: 9781617296130
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Learn Quantum Computing with Python and Q# introduces quantum computing from a practical perspective.

Summary

Learn Quantum Computing with Python and Q# demystifies quantum computing. Using Python and the new quantum programming language Q#, you’ll build your own quantum simulator and apply quantum programming techniques to real-world examples including cryptography and chemical analysis.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the technology

Quantum computers present a radical leap in speed and computing power. Improved scientific simulations and new frontiers in cryptography that are impossible with classical computing may soon be in reach. Microsoft’s Quantum Development Kit and the Q# language give you the tools to experiment with quantum computing without knowing advanced math or theoretical physics.

About the book

Learn Quantum Computing with Python and Q# introduces quantum computing from a practical perspective. Use Python to build your own quantum simulator and take advantage of Microsoft’s open source tools to fine-tune quantum algorithms. The authors explain complex math and theory through stories, visuals, and games. You’ll learn to apply quantum to real-world applications, such as sending secret messages and solving chemistry problems.

What's inside

    The underlying mechanics of quantum computers
    Simulating qubits in Python
    Exploring quantum algorithms with Q#
    Applying quantum computing to chemistry, arithmetic, and data

About the reader

For software developers. No prior experience with quantum computing required.

About the author

Dr. Sarah Kaiser works at the Unitary Fund, a non-profit organization supporting the quantum open-source ecosystem, and is an expert in building quantum tech in the lab. Dr. Christopher Granade works in the Quantum Systems group at Microsoft, and is an expert in characterizing quantum devices.

Table of Contents

PART 1 GETTING STARTED WITH QUANTUM
1 Introducing quantum computing
2 Qubits: The building blocks
3 Sharing secrets with quantum key distribution
4 Nonlocal games: Working with multiple qubits
5 Nonlocal games: Implementing a multi-qubit simulator
6 Teleportation and entanglement: Moving quantum data around
PART 2 PROGRAMMING QUANTUM ALGORITHMS IN Q#
7 Changing the odds: An introduction to Q#
8 What is a quantum algorithm?
9 Quantum sensing: It’s not just a phase
PART 3 APPLIED QUANTUM COMPUTING
10 Solving chemistry problems with quantum computers
11 Searching with quantum computers
12 Arithmetic with quantum computers

About the Author

Dr. Sarah Kaiser completed her PhD in physics (quantum information) at the University of Waterloo's Institute for Quantum Computing. She has spent much of her career developing new quantum hardware in the lab, from satellites to hacking quantum cryptography hardware. Communicating what is so exciting about quantum is her passion, and she loves building new demos and tools to help enable the quantum community to grow. When not at the keyboard, she loves kayaking and writing books about engineering for all ages. 

Dr. Chris Granade completed their PhD in physics (quantum information) at the University of Waterloo's Institute for Quantum Computing, and now works in the Quantum Architectures and Computation (QuArC) group at Microsoft. They work in developing the standard libraries for Q# and is an expert in the statistical characterization of quantum devices from classical data. Previously, Chris helped Scott Aaronson prepare lectures into his recent book, Quantum Computing Since Democritus.