Book Image

Quantum Computing in Practice with Qiskit® and IBM Quantum Experience®

By : Hassi Norlen
5 (1)
Book Image

Quantum Computing in Practice with Qiskit® and IBM Quantum Experience®

5 (1)
By: Hassi Norlen

Overview of this book

IBM Quantum Experience® 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® and Qiskit®, 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®, 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® 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® 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® and Qiskit® with Python.
Table of Contents (12 chapters)

Exploring quantum phase kickback

In this first recipe, we will take a closer look at a staple component of many quantum algorithms, quantum phase kickback, which is used to let one or more qubits pick up the phase angle of a second qubit without changing that second qubit. In the Building the Grover algorithm recipe, we will use phase kickback to identify the correct solution for our search and to amplify the probability of measuring that solution.

This recipe will require a little bit of math to explain some pretty unintuitive aspects of the process and results, but we'll walk through it. It is a really good starting point for the mind-blowing aspects of quantum algorithms.

Getting ready

The sample code for this recipe can be found here: https://github.com/PacktPublishing/Quantum-Computing-in-Practice-with-Qiskit-and-IBM-Quantum-Experience/blob/master/Chapter09/ch9_r1_kickback.py.

The recipe in itself is pretty simple and consists of a set of steps that will walk...