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Introduction to Quantum Computing with Q# and QDK (Hardcover, 1st ed. 2022)
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Introduction to Quantum Computing with Q# and QDK (Hardcover, 1st ed. 2022)
Series: Quantum Science and Technology
Expected to ship within 12 - 17 working days
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This book introduces the fundamentals of the theory of quantum
computing, illustrated with code samples written in Q#, a
quantum-specific programming language, and its related Quantum
Development Kit. Quantum computing (QC) is a multidisciplinary
field that sits at the intersection of quantum physics, quantum
information theory, computer science and mathematics, and which may
revolutionize the world of computing and software engineering. The
book begins by covering historical aspects of quantum theory and
quantum computing, as well as offers a gentle, algebra-based,
introduction to quantum mechanics, specifically focusing on
concepts essential for the field of quantum programming. Quantum
state description, state evolution, quantum measurement and the
Bell's theorem are among the topics covered. The readers also get a
tour of the features of Q# and familiarize themselves with the QDK.
Next, the core QC topics are discussed, complete with the necessary
mathematical formalism. This includes the notions of qubit, quantum
gates and quantum circuits. In addition to that, the book provides
a detailed treatment of a series of important concepts from quantum
information theory, in particular entanglement and the no-cloning
theorem, followed by discussion about quantum key distribution and
its various protocols. Finally, the canon of most important QC
algorithms and algorithmic techniques is covered in-depth - from
the Deutsch-Jozsa algorithm, through Grover's search, to Quantum
Fourier Transform, quantum phase estimation and Shor's algorithm.
The book is an accessible introduction into the vibrant and
fascinating field of quantum computing, offering a blend of
academic diligence with pragmatism that is so central to software
development world. All of the discussed theoretical aspects of QC
are accompanied by runnable code examples, providing the reader
with two different angles - mathematical and programmatic - of
looking at the same problem space.
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