Combinatorial Optimization Using Quantum Computing
A Gentle Introduction
Series: Natural Computing Series;
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Product details:
- Publisher Springer Nature Singapore
- Date of Publication 29 August 2026
- ISBN 9789819588947
- Binding Hardback
- No. of pages301 pages
- Size 235x155 mm
- Language English
- Illustrations X, 301 p. 96 illus., 60 illus. in color. 700
Categories
Long description:
This book provides a comprehensive introduction to quantum optimization, bridging quantum computing and combinatorial optimization for readers without prior background in quantum mechanics. It covers both the theoretical foundations and practical implementation of optimization problems on current quantum hardware.
The book is organized in three parts: Part I (Foundations) introduces essential concepts in quantum computing and combinatorial optimization, establishing the mathematical and computational framework needed for subsequent chapters. Part II (Methodologies) covers the two main quantum computing paradigms: quantum annealing (as implemented on D-Wave systems) and gate-based quantum computing (including variational algorithms such as QAOA and VQE). Part III (Applications and Tools) presents practical case studies and implementation details, including executable code that readers can study, modify, and apply to their own problems. Each chapter emphasizes clear explanations and worked examples. Where appropriate, chapters include code implementations using standard quantum computing frameworks, enabling readers to experiment with algorithms on simulators and actual quantum hardware.
The book is intended for researchers, graduate students, and practitioners in Optimization, Operations Research, Computer Science, and related fields who seek to understand and apply quantum computing methods to combinatorial optimization problems.
MoreTable of Contents:
Foundations of Quantum Computing.- Introduction to combinatorial optimization.- Quantum Annealing for Combinatorial Optimisation.- Problem modelling and quadratic unconstrained
binary optimization.- Quantum Computing in Gate-Based Quantum Computers.- Quantum Optimization Algorithms.- Quantum Optimization Applications.- QoverC: A Profiler of Quantum Computer Simulators for Quantum Optimisation.- Contemporary Challenges of Quantum Combinatorial Optimization.
