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“This isn't just another theoretical quantum computing textbook. It's a hands-on, practical guide that bridges the gap between abstract quantum concepts and real-world applications."- Robert Loredo, former Worldwide Team Leader for IBM’s Quantum Ambassador program.

“If you’re new to quantum computing, have not worked through other textbooks, or want a gentle but comprehensive starting point, this book is an excellent choice."- Alex Khan, VP of Quantum R&D BQP

Key Features

• Understand the theoretical foundations of quantum computing
• Learn how to use the Qiskit framework and how to run quantum algorithms with it
• Discover top quantum algorithms like Grover’s search and Shor’s factoring methods
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

This book is a from-scratch introduction to quantum computing and its most important foundational algorithms, from simple protocols like Deutsch’s algorithm to powerful ones such as Shor’s factoring algorithm. It provides clear explanations and a hands-on approach, with runnable code for both simulators and real quantum hardware. The book is fully self-contained and assumes no prior experience in quantum computing. Starting with a single qubit, it gradually builds up to algorithms that use superposition and entanglement.

Practical applications are presented throughout, including quantum money that cannot be forged, unbreakable quantum cryptography, and quantum algorithms for searching and factoring that significantly outperform classical approaches. All algorithms are implemented and carefully explained using Qiskit 2.1.

By the end of the book, you will understand how quantum algorithms work, how to write your own quantum programs, and how to run them on simulators and real quantum computers, preparing you to move on to advanced topics such as quantum optimization and quantum artificial intelligence.

What you will learn

• Understand what makes a quantum computer unique
• Mathematically represent the state of multi-qubit systems
• Describe the effects of measurements in quantum computers
• Know how quantum superposition, entanglement, and interference work
• Implement and run any quantum algorithm in Qiskit
• Understand how Shor's and Grover's algorithms work
• Gain familiarity with quantum fault-tolerance and quantum advantage

Who this book is for

This book would be ideal for university-level students in Computer Science, Mathematics, Physics or other STEM fields taking introductory-level courses on quantum computing. It also suits professionals, researchers and self-learners with a STEM background.

Table of Contents

1. What Is (and What Is Not) a Quantum Computer?
2. Qubits, Gates, and Measurements
3. Applications and Protocols with One Qubit
4. Coding One-Qubit Protocols in Qiskit
5. How to Work with Two Qubits
6. Applications and Protocols with Two Qubits
7. Coding Two-Qubit Algorithms in Qiskit
8. How to Work with Many Qubits
9. The Full Power of Quantum Algorithms
10. Coding with Many Qubits in Qiskit
11. Finding the Period and Factoring Numbers
12. Searching and Counting with a Quantum Computer
13. Coding Shor and Grover's Algorithms in Qiskit
14. Quantum Error Correction and Fault Tolerance
15. Experiments for Quantum Advantage
16. Appendices

Elías F. Combarro holds degrees in both Mathematics (1997, second highest grades in Spain) and Computer Science (2002, highest grades in Spain). After some research visits at the Novosibirsk State University (Russia), he obtained a Ph.D. in Mathematics (2001). Since 2023, Elías F. Combarro has been a full professor at the Computer Science Department of the University of Oviedo (Spain). He has been a visiting scientist at CERN and Harvard University. Currently, he is Spain representative in the Advisory Board of CERN Quantum Technology Initiative, a member of the Advisory Board of SheQuantum and one of the founders of QSpain. He is one of the authors of A Practical Guide to Quantum Machine Learning and Quantum Optimization (Packt, 2023).

Samuel González-Castillo holds degrees from the University of Oviedo (Spain) in Mathematics and Physics (2021) and a Research Master's Degree in Mathematics from Maynooth University (2023). He is a mathematics research student and graduate teaching assistant at the University of Oviedo, focusing on applying algebraic techniques to problems in quantum computing. In 2021, he developed a benchmarking framework for quantum simulators at CERN openlab. He has contributed to several conferences on quantum computing, including the Quantum Technology International Conference and the Conference on Computing in High Energy and Nuclear Physics. He is the co-author of A Practical Guide to Quantum Machine Learning and Quantum Optimization (Packt, 2023).