Quantum Computing in Practice with Qiskit(R) and IBM Quantum Experience(R): Practical recipes for quantum computer coding at the gate and algorithm le

Understand the nuances of programming traditional quantum computers and solve the challenges of the future while building and executing quantum programs on IBM Quantum hardware and simulators

Key Features

• Work your way up from writing a simple quantum program to programming complex quantum algorithms
• Explore the probabilistic nature of qubits by performing quantum coin tosses and using random number generators
• Delve into quantum algorithms and their practical applications in various domains

Long Description

IBM Quantum Experience(R) is a leading platform for programming quantum computers and implementing quantum solutions directly on the cloud. This book will help you get up to speed with programming quantum computers and provide solutions to the most common problems and challenges.

You'll start with a high-level overview of IBM Quantum Experience(R) and Qiskit(R), where you will perform the installation while writing some basic quantum programs. This introduction puts less emphasis on the theoretical framework and more emphasis on recent developments such as Shor's algorithm and Grover's algorithm. Next, you'll delve into Qiskit(R), a quantum information science toolkit, and its constituent packages such as Terra, Aer, Ignis, and Aqua. You'll cover these packages in detail, exploring their benefits and use cases. Later, you'll discover various quantum gates that Qiskit(R) offers and even deconstruct a quantum program with their help, before going on to compare Noisy Intermediate-Scale Quantum (NISQ) and Universal Fault-Tolerant quantum computing using simulators and actual hardware. Finally, you'll explore quantum algorithms and understand how they differ from classical algorithms, along with learning how to use pre-packaged algorithms in Qiskit(R) Aqua.

By the end of this quantum computing book, you'll be able to build and execute your own quantum programs using IBM Quantum Experience(R) and Qiskit(R) with Python.

What You Will Learn

• Visualize a qubit in Python and understand the concept of superposition
• Install a local Qiskit(R) simulator and connect to actual quantum hardware
• Compose quantum programs at the level of circuits using Qiskit(R) Terra
• Compare and contrast Noisy Intermediate-Scale Quantum computing (NISQ) and Universal Fault-Tolerant quantum computing using simulators and IBM Quantum(R) hardware
• Mitigate noise in quantum circuits and systems using Qiskit(R) Ignis
• Understand the difference between classical and quantum algorithms by implementing Grover's algorithm in Qiskit(R)

Who this book is for

This book is for developers, data scientists, machine learning researchers, or quantum computing enthusiasts who want to understand how to use IBM Quantum Experience(R) and Qiskit(R) to implement quantum solutions and gain practical quantum computing experience. Python programming experience is a must to grasp the concepts covered in the book more effectively. Basic knowledge of quantum computing will also be beneficial.

Author: Hassi Norlén
Publisher: Packt Publishing
Published: 11/20/2020
Pages: 408
Binding Type: Paperback
Weight: 1.54lbs
Size: 9.25h x 7.50w x 0.84d
ISBN: 9781838828448

About the Author
Norlén, Hassi: - Hassi Norlén is an educator, physicist, and software developer, long fascinated with computer programming, both small and large, new and old. He stumbled into the quantum-computing universe a few short years ago and has since then been lucky enough to engage in this fascinating field both professionally and as a hobby. In his day job with IBM, he designs content in the AI Applications division. In his spare time, he spreads the word on the Qiskit(R) open source SDK and quantum computing as an IBM Quantum Ambassador and Qiskit Advocate: lecturing, coding, and hosting quantum-computing workshops. He traces his roots back to Sweden, with the United States being his recently adopted homeland, and is currently enjoying the Bavarian Alps in southern Germany on an IBM Global assignment.

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