Discover the foundations of classical and quantum information theory in the digital age with this modern introductory textbook. Familiarise yourself with core topics such as uncertainty, correlation, and entanglement before exploring modern techniques and concepts including tensor networks, quantum circuits and quantum discord. Deepen your understanding and extend your skills with over 250 thought-provoking end-of-chapter problems, with solutions for instructors, and explore curated further reading. Understand how abstract concepts connect to real-world scenarios with over 400 examples, including numerical and conceptual illustrations, and emphasising practical applications. Build confidence as chapters progressively increase in complexity, alternating between classic and quantum systems. This is the ideal textbook for senior undergraduate and graduate students in electrical engineering, computer science, and applied mathematics, looking to master the essentials of contemporary information theory.
Arvustused
'Professor Simeone presents a comprehensive synthesis of classical and quantum information theory, bridging foundational principles with modern perspectives. This book provides students and researchers with the essential foundations for exploring the central role of information theory in signal processing and communications, as well as its emerging quantum dimensions. The presentation is very well organized pedagogically, with clear learning objectives and exposition of needed background materials throughout.' Vincent Poor, Princeton University 'In this most timely book, Osvaldo Simeone masterfully unifies classical and quantum perspectives on information theory, offering clarity and depth that will inspire both students and researchers. This book addressing Classical and Quantum Information Theory, provides a rigorous yet highly accessible guide to a field that underpins engineering, computer science, and the sciences at large.' Shlomo Shamai Shitz, Technion Israel Institute of Technology 'I thought there was no longer any gap left in the literature of information theory for another fundamental book, but here it is, innovatively juxtaposing classical and quantum theory' Lajos Hanzo, University of Southampton
Muu info
Discover the foundations of classical and quantum information theory in the digital age with this modern introductory textbook.
Preface; References; Acknowledgements; Notations; Acronyms; Part I.
Classical Information:
1. Uncertainty, information, and entropy;
2.
Information quantification by asking, compressing, or sampling: Shannon
entropy;
3. Information quantification by predicting or guessing: Tsallis
entropy and Rényi entropy;
4. Relative entropy; Part II. Quantum Information:
5. From classical to quantum information;
6. Quantum uncertainty: measured
entropy, coherence, and the uncertainty principle;
7. Classical and quantum
uncertainty: mixed states and quantum entropy;
8. Quantum relative entropy;
Part III. Dynamic Information:
9. Dynamic classical information;
10. Quantum
dynamic information in closed systems;
11. Quantum dynamic information in
open systems; Part IV. Bipartite Classical Information:
12. Bipartite
classical information as correlation;
13. Bipartite classical information via
residual uncertainty; Part V. Bipartite Quantum Information:
14. Bipartite
classical and quantum Information for pure states;
15. Bipartite dynamic
classical and quantum information for pure states;
16. Bipartite quantum and
classical information for mixed states; Part VI. Multipartite Classical and
Quantum Information:
17. A brief introduction to tensor networks;
18.
Multipartite classical information: fragmentation, scale, and strength;
19.
Multipartite classical information: structure;
20. Multipartite quantum
information: fragmentation, scale, and strength;
21. Multipartite quantum
information: structure; Index.
Osvaldo Simeone is a Professor of Information Engineering at King's College London, where he co-directs the Centre for Intelligent Information Processing Systems. He is the author of Machine Learning for Engineers (2022) and of several monographs. He is the recipient of a number of best paper awards, and he is a Fellow of the IEEE, EPSRC, and IET.
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