Mathematical Foundations of Quantum Computing: A Scaffolding Approach (eBook)

(Imported from Amazon) This book is a learned and thorough exposition of the mathematics that supports quantum computing.
The authors have gone to great lengths to make it both learner-friendly and detailed while maintaining rigor. It covers topics ranging from the fundamentals of quantum mathematics to the complexities of vector and matrix algebra, as well as the probabilities central to quantum computing. The text is complemented by numerous supporting figures that effectively illustrate key concepts. Applications of quantum computing are introduced and seamlessly integrated throughout the book. This volume, along with its companion, Quantum Computing and Information - a Scaffolding Approach, is an essential addition to the bookshelf of anyone seeking a deeper understanding of quantum computing and its mathematical foundations.

(Imported from Amazon) great textbook, very sturdy. actually a really good textbook

(Imported from Amazon) This is the second book of the scaffolding series in quantum computing by the authors. I've read the first one (QCI) and it impressed me a lot. In my opinion this second book also hits the target - it can serve as a math reference at all levels in quantum computing which is somehow currently lacking in the market.
If one tries to read any quantum computing books for "beginners", it is nearly unavoidable that they soon (typically within 20 pages into the book) find themselves encountering math that is rarely used in fields other than quantum physics, such as matrices and vectors comprising complex numbers and the strange-looking Dirac notation. For those who have never seen those before, it can be truly intimidating. But unfortunately, the quantum stuff is too weird (if not impossible) to be explained without using those tools. Actually, Dirac notation is such a smart invention that it makes understanding quantum stuff much easier (than without using it).
However, before this book, a specific math reference for quantum computing is rarely done. The math introduction for quantum computing books is typically too brief for beginners (I've read multiple books trying to explain all the required math in 20 or so pages), and general linear algebra textbooks is not specific to quantum computing so they are not very useful, either. But this book fills the blank. It is a detailed, accessible math book specific to quantum computing.
I found that a good feature of this book is to introduce contents in a progressive and reference-serving manner that fits all levels of readers. A reader can start from any part depending on the foundation level. Part One gives important preliminaries - sets, functions, trigonometry and complex numbers. Part Two introduces basic linear algebra covered in most textbooks but with complex components and Dirac notation. Part Three covers the more advanced quantum computing-specific math tools. Part Four is probability theory basics that is also intrinsic for the quantum world.
I think the book is written in a way that matches its scaffolding approach. It is quite accessible to read. As long as the reader has a solid math foundation from high school, the book can be accessible with so many examples and exercises. Along with the first book of the series, they can altogether serve as a quite good starting point for those who hope to seriously understand quantum computing in a rigorous way. I am looking forward to their third book (the quantum algorithm one).

(Imported from Amazon) The purchase process was smooth and delivery was fast and on time. The book I bought is exactly I expected. A well written book on quantum computing with a high degree of pedagogical explanation and a fair price.

(Imported from Amazon) El libro llegó dañado, por el pésimo empaque, no tienen el más mínimo cuidado, además el libro en la editorial está en color, y el que me llegó es el más caro (pasta dura) y la impresión es en blanco y negro. Estoy muy molesto.

(Imported from Amazon) The book is in excellent condition.

(Imported from Amazon) The book isn't compatible with the Kindle Scribe which is ridiculous!

(Imported from Amazon) Bought as a graduation present for my grandson in lew of a card.
He loved it!

(Imported from Amazon) I found this book incredibly helpful. Just right for my beginning study on quantum computing. Recommended!

(Imported from Amazon) Worth to have one on hand.

(Imported from Amazon) An educator's approach to quantum computing. Includes detailed explanations, accompanied by worked examples of notations, vectors, linear spaces, matrix methods, and fundamental concepts in quantum probability such as the Markov Chains. Definitely a great reference for those interested in the quantum world.

(Imported from Amazon) I appreciate the scaffolded approach presented in the book. The examples are great, and they quickly build upon prior ones. If the evolution of computing is about to take a leap forward, this text will help more people grasp the concepts and even participate in these exciting advances in technology.

(Imported from Amazon) This book is a concise and complete mathematical foundation for quantum computing.

(Imported from Amazon) Mathematical Foundations of Quantum Computing offers a rigorous yet accessible mathematical foundation tailored for quantum computing, emphasizing essential topics like linear algebra, complex analysis, and probability while excluding less relevant areas such as differential equations. The book’s early use of Dirac notation, Pauli matrices, and tensor products reflects its alignment with quantum computing's core demands. Its scaffolding pedagogy ensures a clear progression from basic concepts to advanced topics such as spectral decomposition and Monte Carlo methods, enhanced by problem sets and level indicators for diverse learners. The text is well-structured into four focused parts—preliminaries, vectors/matrices, matrix methods, and probability—balancing breadth and depth. It bridges theory and practice by presenting matrices as dynamic operators and incorporating real-world tools like the Schmidt decomposition and MCMC methods. Contributions from interdisciplinary experts and the inclusion of appendices and key formulas further enhance its value as both a textbook and reference. This volume stands alone as a self-contained resource while preparing readers for further study in quantum algorithms. Overall, it excels in clarity, depth, and educational design, making it a vital resource for students, instructors, and researchers in quantum computing.