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)

A quick interlude on classical search

Before we hit the Grover algorithm, let's just take a quick peek at a standard, classical linear search algorithm. For a classical algorithm that searches an unordered database, the average number of times you have to look for a given entry is of the order of where N is the number of items in the database. For example, if your unordered database has four items, you will generally have to look an average of two times to find your item.

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_r2_classic_search.py.

How to do it…

Let's search for a specific two-bit entry in a small database with four items:

  1. First, we need to enter the two-bit string that we are searching for, and then the number of searches to try to get some statistics:
    Searching in a scrambled database with...