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Weitersagen:


Herausgeber: 
  • Alberto Moraglio
  • Francisco Chicano
  • Ofer M. Shir
  • Combinatorial Optimization Using Quantum Computing: A Gentle Introduction 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Vorankündigung
    Veröffentlichung:  ANGEKÜNDIGT (September 2026)  
    Genre:  EDV / Informatik 
     
    combinatorial optimization / Discrete Mathematics in Computer Science / Discrete Optimization / Diskrete Mathematik / Optimierung / Quadratic Unconstrained Binary Optimization / Quantenphysik (Quantenmechanik und Quantenfeldtheorie) / Quantum Annealing
    ISBN:  9789819588947 
    EAN-Code: 
    9789819588947 
    Verlag:  Springer EN 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Seiten:  301 
    Illustration:  X, 301 p. 96 illus., 60 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Keine Bewertung vor Veröffentlichung möglich.
    Inhalt:
    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.

      



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