Book Review: Quantum Computing with Python and IBM Quantum (Second Edition) by Robert Loredo

Overview

Robert Loredo’s Quantum Computing with Python and IBM Quantum (Second Edition) is an updated and refined version of its predecessor, offering a structured introduction to IBM’s Qiskit tools. The book serves as an accessible entry point for beginners interested in quantum computing, especially those looking to understand the practical aspects of quantum circuits and algorithms without getting overwhelmed by heavy mathematical formalism.

This second edition aligns with IBM’s latest advancements in quantum computing, incorporating changes in terminology and methodologies related to transpilation, error mitigation, and quantum primitives. The updates reflect IBM’s shift toward more scalable quantum architectures, including 56-qubit systems and the 127-qubit Eagle processor.

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Key Features

1. Clear and Concise Introduction The book remains an excellent starting point for those new to quantum computing, providing a clean and simplified treatment of fundamental concepts. The introductory chapters do a great job of explaining qubits, quantum states, and quantum circuits in a way that is approachable for readers with a basic background in computing.
2. Balance Between Theory and Practice While some books on quantum computing lean too heavily into theory or programming, Quantum Computing with Python and IBM Quantum maintains a balanced approach. It provides enough mathematical background to understand quantum principles but keeps the focus on practical implementation through simple examples in Python and Qiskit.
3. Updated Content with IBM’s Latest Tools The book integrates IBM’s new terminology and methodologies, ensuring that readers are working with the latest developments in Qiskit. Updates on transpilation strategies and error mitigation techniques, including TREX (Tensored Readout Error eXtinction) and quantum primitives, provide insights into IBM’s efforts to improve quantum computation accuracy and performance. A shift in focus toward IBM’s larger quantum processors (such as the 56-qubit and the 127-qubit Eagle processor) demonstrates IBM’s move toward more powerful quantum systems, helping readers prepare for a future with larger-scale quantum computing.
4. Hands-On Approach with Python & Qiskit The book includes detailed walkthroughs on installing Qiskit, writing quantum circuits, and running them on real quantum hardware. This hands-on approach ensures that readers can experiment with quantum computing concepts in a tangible way.
5. Simplified Explanation of Algorithms The book covers fundamental quantum algorithms such as the Quantum Fourier Transform (QFT) and Grover’s Search, presenting them in a way that doesn’t overwhelm first-time learners. Readers can see how these algorithms are implemented in Qiskit, making it easier to bridge the gap between theory and application.

Quantum Computing with Python and IBM Quantum (Second Edition) is a well-structured, beginner-friendly guide that effectively introduces readers to quantum computing with Python and Qiskit. The updates in this edition ensure that learners are working with IBM’s latest quantum tools, making it a valuable resource for those looking to get started with practical quantum programming.