Quantum computers offer a potential sea change in computing power. IBM Research has made quantum computing available to the public for the first time, providing access to IBM QX from any desktop or mobile device via the cloud. Complete with cutting-edge practical scenarios, this book will help you understand the power of quantum computing by programming for the real-world.
Mastering Quantum Computing with IBM QX begins with an introduction to the concept and principles of quantum computing and the areas in which they can be applied. You'll see how quantum computing can be used to improve the classical methods of computer processing and convert a classical algorithm into a quantum algorithm. You'll then explore the IBM ecosystem, which facilitates quantum development with the help of the Quantum Composer and Qiskit. As you progress through the chapters, you'll learn how to implement algorithms on the quantum processor and how quantum computations are actually performed.
By the end of the book, you'll have learned how to create quantum programs of your own, explored the impact of quantum computing on your business and career, and future-proofed your programming career.
If you're a developer or data scientist interested in learning quantum computing, this book is for you. You're expected to have basic understanding of the Python language, but knowledge of physics, quantum mechanics, or advanced mathematics is not required.
Chapter 1, What is Quantum Computing?, gives an overview of what quantum computing is in contrast to classical computing, focusing on its potential advantages over classical computers. We then go over the history of classical and quantum computing and get an overview of the state-of-the-art in computation.
Chapter 2, Qubits, gives us an overview of why qubits are the cornerstones of quantum computation along with code to simulate it in Python. It discusses superposition and uses Python code to explore three different representations of a single qubit. The chapter then introduces the Bloch sphere and describes the superposition and measurement of single qubits.
Chapter 3, Quantum States, Quantum Registers, and Measurement, is about the quantum version of classic registers, quantum registers, which hold quantum states. We will discuss separable states and entanglement, which leads to a focus on quantum measurement and a Python implementation of quantum measurement for multiple, possibly entangled, qubits.
Chapter 4, Evolving Quantum States with Quantum Gates, gives an overview of the most commonly-used gates in quantum computing: I, X, Y, Z, H, S, S†, T, T†, and CNOT, which form a universal gate set that can be combined to perform any quantum computation. It provides a Python implementation of these commonly used quantum gates, and goes over examples within Python of these gates being applied to the states we have examined so far.
Chapter 5, Quantum Circuits, expands on the idea of quantum gates to introduce quantum circuits, the quantum analogue of classical circuits. It goes over how classical gates can be reproduced by quantum circuits and proceeds to introduce a visual representation of quantum circuits that can be used to easily define a quantum circuit without reference to mathematics or use of a programming language.
Chapter 6, The Quantum Composer, is all about the interactive interface in IBM QX used to create quantum circuits via quantum scores, the graphical manner of representing circuits introduced earlier. Via the Quantum Composer, you can define your own circuits for implementation on the IBM QX hardware or software simulator. The chapter proceeds to translate the examples previously coded in Python to the Quantum Composer representation and gives you the opportunity to run them on IBM QX hardware.
Chapter 7, Working with OpenQASM, describes the Open Quantum Assembly Language (pronounced open kazm). This language can be used within IBM QX. The chapter revisits some of the quantum circuits defined in previous chapters and redefines them within the OpenQASM language. It then provides you with the opportunity to rerun these circuits on the IBM QX, using OpenQASM.
Chapter 8, Qiskit and Quantum Computer Simulation, introduces Qiskit (Quantum Information Software Kit), focusing on how it can be used to run programs in IBM QX via the cloud, as well as its capabilities for quantum simulation. The chapter then moves on to a capstone project using Qiskit to illustrate, in one project, the concepts of quantum circuits, measurement, and Qiskit usage, while producing a useful demo of using a quantum computer to represent musical chords.
Chapter 9, Quantum AND (Toffoli) Gates and Quantum OR Gates, explores some of the quantum equivalents of classic Boolean logical gates in order to specify logic problems to be solved by a quantum computer for use with Grover's algorithm and other algorithms.
Chapter 10, Grover's Algorithm, goes over the classical implementation compared to the quantum implementation as given by Grover's algorithm. Finally, the chapter provides an implementation of Grover's algorithm in OpenQASM, Qiskit, and quantum score.
Chapter 11, Quantum Fourier Transform, describes the Quantum Fourier Transform, which is a sub-routine of many important quantum algorithms, including Shor's algorithm. The chapter next shows the use a classical algorithm to compute the discrete Fourier transform, that is a Fourier transform of a signal represented on a classical computer. Finally, a Quantum Fourier Transform algorithm is given in OpenQASM, Qiskit, and quantum score.
Chapter 12, Shor's Algorithm, explores Shor's algorithm. It goes over what prime factorization is, the classical implementation of an algorithm to perform prime factorization as compared to the quantum implementation as given by Shor's algorithm. Finally, the chapter provides an implementation of Shor's algorithm in Qiskit.
Chapter 13, Quantum Error Correction, describes the problem of quantum error propagation and illustrates the need for quantum error correction. Next, an overview of quantum error correction (QEC) is given, and finally, the chapter provides an implementation of a simple QEC algorithm.
Chapter 14, Conclusion – The Future of Quantum Computing, reviews what we have learned and places it in the context of areas where quantum computing is poised to disrupt, and those understanding quantum computation and quantum programming are likely to be in high demand. In addition, the book discusses why an executive, a programmer, or a technically minded person who doesn't happen to be a quantum physicist might care about quantum computing.
The solutions to practice questions at the end of each chapter are available at https://www.packtpub.com/sites/default/files/downloads/Assessments.pdf.
This book assumes you are familiar with the Python programming language. Python 3.4+ is used. You won't need knowledge of quantum mechanics, physics, or advanced mathematics, but should have an understanding of algebra at a high-school level. To get the most out of the book, go through the exercises in the Jupyter Notebooks provided and answer the questions posed at the end of each chapter.
You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.
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We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: https://www.packtpub.com/sites/default/files/downloads/9781789136432_ColorImages.pdf.
There are a number of text conventions used throughout this book.
CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "Now open theHello Quantum World.ipynb notebook by navigating to it from the Jupyter Notebook GUI."
A block of code is set as follows:
from qiskit.tools.visualization import plot_histogram plot_histogram(job_exp.result().get_counts(qc))
When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:
import time
q = qiskit.QuantumRegister(5)
c = qiskit.ClassicalRegister(5)
qc = qiskit.QuantumCircuit(q, c)Any command-line input or output is written as follows:
cd Mastering-Quantum-Computing-with-IBM-QXBold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Now, click Simulate, then click OK, and within seconds you will get the output."
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