ZX-Calculus for Quantum Circuits

A Diagrammatic Approach to Quantum Circuit Analysis and Optimization

AvSubhojit Halder

Häftad, Engelska, 2026

551 kr

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ZX-Calculus has emerged as one of the most powerful frameworks for representing and optimizing quantum circuits—bridging the gap between abstract theory and real-world implementation. This book offers a complete and coding-driven introduction to ZX-Calculus, guiding readers from the mathematical and physical foundations of quantum circuits to the advanced techniques of diagrammatic reasoning and circuit optimization. Beginning with qubits, gates, and entanglement, you will gradually go through the principles of ZX-Calculus, spider rules, and diagrammatic equivalences that form the foundation of this visual and rigorous language.Building upon this foundation, the book takes a hands-on approach to applying ZX-Calculus in modern quantum development environments. You will explore open-source tools such as PyZX, Quantomatic, and ZX-Optimizer; learn to translate quantum circuits into diagrams and back; and perform real-world circuit optimizations that reduce resource costs for NISQ devices. Advanced chapters extend these ideas to phase gadgets, Clifford hierarchies, and measurement-based computation, while the final section dives into circuit fabrication from ZX nodes—linking theory directly to implementation.Whether you are a student, researcher, or professional developer, this book equips you with the theoretical insight, coding skills, and practical tools to design, optimize, and deploy efficient quantum circuits using the power of ZX-Calculus.What You Will Learn:Translate complex quantum operations into intuitive diagrammatic forms and simplify them through step-by-step transformationsIntegrate ZX-Calculus concepts into modern quantum computing workflows and frameworksMaster the fundamentals of ZX-Calculus and apply ZX-based methods for large-scale circuit optimizationDiscover how ZX-Calculus can be used in fermionic tensor networks, quantum error correction, and quantum machine learningWho This Book Is For:Researchers, Developers and Post graduate students in Quantum Computing.

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