Learn Quantum Computing with Python and IBM Quantum Experience

A step-by-step guide to learning the implementation and associated methodologies in quantum computing with the help of the IBM Quantum Experience, Qiskit, and Python that will have you up and running and productive in no time

▶Book Description
IBM Quantum Experience is a platform that enables developers to learn the basics of quantum computing by allowing them to run experiments on a quantum computing simulator and a real quantum computer. This book will explain the basic principles of quantum mechanics, the principles involved in quantum computing, and the implementation of quantum algorithms and experiments on IBM's quantum processors.

You will start working with simple programs that illustrate quantum computing principles and slowly work your way up to more complex programs and algorithms that leverage quantum computing. As you build on your knowledge, you'll understand the functionality of IBM Quantum Experience and the various resources it offers. Furthermore, you'll not only learn the differences between the various quantum computers but also the various simulators available. Later, you'll explore the basics of quantum computing, quantum volume, and a few basic algorithms, all while optimally using the resources available on IBM Quantum Experience.

By the end of this book, you'll learn how to build quantum programs on your own and have gained practical quantum computing skills that you can apply to your business.

▶What You Will Learn
⦁Explore quantum computational principles such as superposition and quantum entanglement
⦁Become familiar with the contents and layout of the IBM Quantum Experience
⦁Understand quantum gates and how they operate on qubits
⦁Discover the quantum information science kit and its elements such as Terra and Aer
⦁Get to grips with quantum algorithms such as Bell State, Deutsch-Jozsa, Grover's algorithm, and Shor's algorithm
⦁How to create and visualize a quantum circuit

▶Key Features
⦁Determine the difference between classical computers and quantum computers
⦁Understand the quantum computational principles such as superposition and entanglement and how they are leveraged on IBM Quantum Experience systems
⦁Run your own quantum experiments and applications by integrating with Qiskit

▶Who This Book Is For
This book is for Python developers who are looking to learn quantum computing and put their knowledge to use in practical situations with the help of IBM Quantum Experience. Some background in computer science and high-school-level physics and math is required.

▶What this book covers
⦁ Chapter 1, Exploring the IBM Quantum Experience, will be your guide to the IBM Q Experience dashboard. This chapter will describe the layout and what each section in the dashboard means. The dashboard might alter over time, but the basic information should still be available to you.

⦁ Chapter 2, Circuit Composer – Creating a Quantum Circuit, will help you learn about Circuit Composer. This chapter will outline the user interface that will assist you in learning about quantum circuits, the qubits, and their gates that are used to perform operations on each qubit.

⦁ Chapter 3, Creating Quantum Circuits Using Quantum Lab Notebooks, will help you learn how to create circuits using the Notebook with the latest version of Qiskit already installed on the IBM Quantum Experience. You will learn how to save, import, and leverage existing circuits without having to install anything on your local machine.

⦁ Chapter 4, Understanding Basic Quantum Computing Principles, will help you learn about the basic quantum computing principles used by the IBM Quantum systems, particularly, superposition, entanglement, and interference. These three properties, often used together, serve as the base differentiators that separate quantum systems from classical systems.

⦁ Chapter 5, Understanding the Quantum Bit (Qubit), will help you learn about the basic fundamental component of a quantum system, the quantum bit or qubit, as it is often called. After reading this chapter, you will understand the basis states of a qubit, how they are measured, and how they can be visualized both mathematically and graphically.

⦁ Chapter 6, Understanding Quantum Logic Gates, will help you learn how to perform operations on a qubit. These operations are often referred to as quantum gates. This chapter will enable you, via the IBM Quantum Experience, to get to grips with the operations that each of these quantum gates performs on a qubit and the results of each of those operations. Examples of the quantum principles such as reversibility, which is a core principle for all quantum gates, will be included.

⦁ Chapter 7, Introducing Qiskit and its Elements, will help you learn about Qiskit and all of its libraries that can help you develop and implement various quantum computing solutions. Qiskit is composed of four elements, each of which has a specific functionality and role that can be leveraged based on the areas you wish to experiment in. The elements are Terra (Earth), Aer (Air), Ignis (Fire), and Aqua (Water). This chapter will also discuss how to contribute to each of the elements and how to install it locally on your machine.

⦁ Chapter 8, Programming with Qiskit Terra, will help you learn about the basic foundational element, Terra. Terra is the base library upon which all the other elements of Qiskit are built. Terra allows a developer to code the base of an algorithm to the specific operator on a qubit. This is analogous to assembly language with just a slightly easier set of library functions. It will also include a section on the Pulse library, which allows you to create pulse schedules to manipulate the quantum qubits via the hardware.

⦁ Chapter 9, Monitoring and Optimizing Quantum Circuits, will help you learn how to monitor the job requests sent to either the simulator or the quantum computers on the IBM Quantum Experience. Optimization features will also be covered here to allow you to leverage many of the existing optimization features included in the Qiskit libraries or to create your own custom optimizers.

⦁ Chapter 10, Executing Circuits Using Qiskit Aer, will help you learn about Qiskit Aer, a high-performance framework that you will use to simulate your circuits on various optimized simulator backends. You will learn what the differences are between the four various simulators of Qasm, State vector, Unitary, and Pulse, and what functionality each one exhibits. Aer also contains tools you can use to construct noise models, should you need to perform some research to reproduce errors due to noise.

⦁ Chapter 11, Mitigating Quantum Errors Using Ignis, will help you learn about the various errors that currently affect experiments on read devices, such as relaxation and decoherence, so you can design quantum error correction codes. You will also learn about readout error mitigation, which is a way to mitigate the readout errors returned from a quantum computer.

⦁ Chapter 12, Learning about Qiskit Aqua, will, in essence, pull everything together so that end users such as researchers and developers from the various domains of chemistry, machine learning, finance, optimization, and more can run their computations on a quantum computer system without having to know all the inner workings. Aqua is the tool connected to quantum algorithms that has been created to do just that. You will learn how to extend your classical application to include running a quantum algorithm.

⦁ Chapter 13, Understanding Quantum Algorithms, will dig into some basic algorithms using the IBM Quantum Experience Composer. This chapter will start with some simple algorithms that illustrate the advantages of superposition and entanglement, such as Bell's state theorem, and extends into some more common algorithms to solve some problems that illustrate uses of superposition and entanglement such as Deutsch-Josza and a few others, each of which provides some variance to the different algorithm types.

⦁ Chapter 14, Applying Quantum Algorithms, describes the various quantum computing properties and algorithms used to create some of the more well-known algorithms such as Quantum Amplitude Estimation, Variational Quantum Eigensolvers, and Shor's algorithm.

⦁ Appendix A, Resources, will help you get familiar with all the available resources in the IBM Quantum Experience and Qiskit community. These resources that have been contributed either by the Qiskit open source community, or the IBM Quantum research teams themselves. The information is laid out so anyone with basic to expert-level knowledge can jump in and start learning. There is a full quantum course, textbook, and Slack community that you can connect to in order to extend your learning and collaborate with others.