A Practical Guide to Quantum Computing. Hands-on approach to quantum computing with Qiskit

Elías F. Combarro, Samuel González-Castillo, Ismael Faro Sertage

This book is an introduction, from scratch, to quantum computing and the most important and foundational quantum algorithms—ranging from humble protocols such as Deutsch’s algorithm to ones with far-reaching potential, such as Shor’s factoring algorithm—offering clear explanations and a hands-on approach with runnable code on simulators and real hardware. The book is self-contained and does not assume any previous experience in quantum computing. Starting with a single qubit, it scales to algorithms using superposition and entanglement.At every step, examples of applications are provided, including how to create quantum money that is impossible to forge, quantum cryptography that cannot be broken, and algorithms for searching and factoring that are much faster than those that regular, non-quantum computers can use. Code for each of these algorithms is provided (and explained in detail) using Qiskit 2.1.After reading this book, you will understand how quantum algorithms work, how to write your own quantum programs, and how to run them on quantum simulators and actual quantum computers. You will also be prepared to take the jump into quantum algorithms for optimization and artificial intelligence, like those presented in our previous book, A Practical Guide to Quantum Machine Learning and Quantum Optimization.

A Practical Guide to Quantum Machine Learning and Quantum Optimization. Hands-on Approach to Modern Quantum Algorithms

Alberto Di Meglio, Elías F. Combarro, Samuel González-Castillo, Alberto Di Meglio

This book provides deep coverage of modern quantum algorithms that can be used to solve real-world problems. You’ll be introduced to quantum computing using a hands-on approach with minimal prerequisites.You’ll discover many algorithms, tools, and methods to model optimization problems with the QUBO and Ising formalisms, and you will find out how to solve optimization problems with quantum annealing, QAOA, Grover Adaptive Search (GAS), and VQE. This book also shows you how to train quantum machine learning models, such as quantum support vector machines, quantum neural networks, and quantum generative adversarial networks. The book takes a straightforward path to help you learn about quantum algorithms, illustrating them with code that’s ready to be run on quantum simulators and actual quantum computers. You’ll also learn how to utilize programming frameworks such as IBM’s Qiskit, Xanadu’s PennyLane, and D-Wave’s Leap.Through reading this book, you will not only build a solid foundation of the fundamentals of quantum computing, but you will also become familiar with a wide variety of modern quantum algorithms. Moreover, this book will give you the programming skills that will enable you to start applying quantum methods to solve practical problems right away.