
Learn Quantum Computing with Python and IBM Quantum
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Chapter 1, Exploring the IBM Quantum Tools, will introduce you to all the tools available to you on the IBM Quantum platform. These tools will help you get up and running quickly and easily without having to install or purchase anything.
Chapter 2, Creating Quantum Circuits with IBM Quantum Composer, discusses this easy-to-use user interface, which is a great tool for visualizing how the various quantum gates and operations affect each qubit and help build an intuitive understanding of the differences between classical and quantum computing.
Chapter 3, Introducing and Installing Qiskit, explores the Quantum Information Science Kit (Qiskit) and its advanced features to develop and implement various quantum algorithms, and noise models. Qiskit has various features that help you build quantum circuits, algorithms, and applications easily and allows you to run them on local simulators and real quantum systems.
Chapter 4, Understanding Basic Quantum Computing Principles, begins our quantum journey by discussing the basic quantum computing principles of superposition, entanglement, and interference, which are used by many quantum algorithms. This will also help you understand what differentiates quantum computing from classical computing.
Chapter 5, Understanding the Qubit, covers what the quantum bit, or qubit, is and how you can manipulate it on a quantum system using the various gates and operators, and how to visualize the results of those operations.
Chapter 6, Understanding Quantum Logic Gates, takes a deeper look at the various quantum gates and operations used to change the state of the qubits and your quantum circuit.
Chapter 7, Programming with Qiskit, is where we start digging into creating quantum circuits using the quantum gates and operations we’ve learned about so far. You will also learn how these gates and operations are converted into microwave pulse schedules, which are what is used to manipulate the qubits on the quantum system.
Chapter 8, Optimizing and Visualizing Quantum Circuits, discusses sending the instructions from your quantum program to run on a quantum system, which has some interesting work happening in the background. Which qubits are the best for running your circuit? Which connections should we select between the qubits that minimizes the number of gates? All these are taken care of by the preset pass manager generator, which we will cover in this chapter.
Chapter 9, Simulating Quantum Systems and Noise Models, explains that all quantum systems, no matter the technology used to create them, must deal with the issue of noise. In this chapter, you will learn what these noises are and how to create models that simulate them to better understand the effects they have on your quantum circuit.
Chapter 10, Suppressing and Mitigating Quantum Noise, explains how to mitigate the various effects noise has on a quantum system.
Chapter 11, Understanding Quantum Algorithms, takes a deep look at the basic quantum algorithms to help understand how the quantum computing principles of superposition, entanglement, and interference are used. We will also review and code some fundamental concepts and algorithms which will help us understand the more complex algorithms.
Chapter 12, Applying Quantum Algorithms, takes you through applying the quantum computing principles and concepts that we’ve learned about to some complex quantum algorithms.
Chapter 13, Understanding Quantum Utility and Qiskit Patterns, covers what quantum utility is and why it is the key to getting us closer towards quantum advantage. It will also provide an overview of the Qiskit patterns and how they can simplify your development experience to build complex quantum circuits.
Appendix A: Resources, provides a list of further resources that you can use to explore the topics covered in this book in more detail.
Appendix B, Assessments, provides the answers to the questions that you will find at the end of each chapter.