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Quantum computing is a rapidly emerging field. As researchers entering the field from outside traditional domains, such as theoretical physics or computer science, we found the landscape both rich and fragmented—dense with promise but dif-ficult to navigate without a cohesive, application-oriented framework. This book was born from our own attempts to cross that threshold from classical computa-tional methods into quantum computing—not as physicists, but as computational engineers—and to build a practical bridge for others who wish to do the same.
While several introductory texts exist, they often assume prior exposure to quantum theory or computational complexity. Our aim is different: to build a bridge from classical engineering and scientific computing to quantum algorithms, without sacrificing technical depth. This book adopts an applied, algorithmic perspective, integrating mathematical foundations, computational models, and real-world applications.
The book is organized into seven parts, each divided into focused chapters. These chapters are intended to be modular and self-contained, allowing instructors or readers to adapt them to different learning paths or interests:
Part I: Mathematical and Computational Preliminaries Foundational material in linear algebra, probability, and numerical methods, tailored to the quantum context.
Part II: A Brief Introduction to Quantum Mechanics Core quantum phenomena presented through key experiments, emphasizing physical intuition.
Part III: Elements of Quantum Computing The computational framework of quantum computing—qubits, gates, circuits, and measurement.
Part IV: Programming Quantum Computers Practical aspects of working with quantum systems, including software stacks, noise, and available libraries.
Part V: Algorithmic Primitives, Subroutines, and Frameworks Reusable algorithmic components that form the building blocks of more advanced methods.
For engineering students and newcomers to quantum computing, Parts I–III provide the necessary foundation, and Parts IV–V introduce core programming and algorithmic tools.
For researchers and advanced practitioners, Parts V–VII offer in-depth treat-ments of quantum algorithmic frameworks and applications, with references to the underlying theory where needed.
For instructors, each chapter can serve as a standalone module in an advanced undergraduate-or graduate-level course. The modular structure allows for flex-ible integration into existing curricula in computing, applied mathematics, or engineering.