Classical and quantum information theory : an introduction for the telecom scientist
著者
書誌事項
Classical and quantum information theory : an introduction for the telecom scientist
Cambridge University Press, 2009
大学図書館所蔵 全25件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
Information theory lies at the heart of modern technology, underpinning all communications, networking, and data storage systems. This book sets out, for the first time, a complete overview of both classical and quantum information theory. Throughout, the reader is introduced to key results without becoming lost in mathematical details. Opening chapters present the basic concepts and various applications of Shannon's entropy, moving on to the core features of quantum information and quantum computing. Topics such as coding, compression, error-correction, cryptography and channel capacity are covered from classical and quantum viewpoints. Employing an informal yet scientifically accurate approach, Desurvire provides the reader with the knowledge to understand quantum gates and circuits. Highly illustrated, with numerous practical examples and end-of-chapter exercises, this text is ideal for graduate students and researchers in electrical engineering and computer science, and practitioners in the telecommunications industry. Further resources and instructor-only solutions are available at www.cambridge.org/9780521881715.
目次
- 1. Probabilities basics
- 2. Probability distributions
- 3. Measuring information
- 4. Entropy
- 5. Mutual information and more entropies
- 6. Differential entropy
- 7. Algorithmic entropy and Kolmogorov complexity
- 8. Information coding
- 9. Optimal coding and compression
- 10. Integer, arithmetic and adaptive coding
- 11. Error correction
- 12. Channel entropy
- 13. Channel capacity and coding theorem
- 14. Gaussian channel and Shannon-Hartley theorem
- 15. Reversible computation
- 16. Quantum bits and quantum gates
- 17. Quantum measurments
- 18. Qubit measurements, superdense coding and quantum teleportation
- 19. Deutsch/Jozsa alorithms and quantum fourier transform
- 20. Shor's factorization algorithm
- 21. Quantum information theory
- 22. Quantum compression
- 23. Quantum channel noise and channel capacity
- 24. Quantum error correction
- 25. Classical and quantum cryptography
- Appendix A. Boltzmann's entropy
- Appendix B. Shannon's entropy
- Appendix C. Maximum entropy of discrete sources
- Appendix D. Markov chains and the second law of thermodynamics
- Appendix E. From discrete to continuous entropy
- Appendix F. Kraft-McMillan inequality
- Appendix G. Overview of data compression standards
- Appendix H. Arithmetic coding algorithm
- Appendix I. Lempel-Ziv distinct parsing
- Appendix J. Error-correction capability of linear block codes
- Appendix K. Capacity of binary communication channels
- Appendix L. Converse proof of the Channel Coding Theorem
- Appendix M. Block sphere representation of the qubit
- Appendix N. Pauli matrices, rotations and unitary operators
- Appendix O. Heisenberg Uncertainty Principle
- Appendix P. Two qubit teleportation
- Appendix Q. Quantum Fourier transform circuit
- Appendix R. Properties of continued fraction expansion
- Appendix S. Computation of inverse Fourier transform in the factoring of N=21 through Shor's algorithm
- Appendix T. Modular arithmetic and Euler's Theorem
- Appendix U. Klein's inequality
- Appendix V. Schmidt decomposition of joint pure states
- Appendix W. State purification
- Appendix X. Holevo bound
- Appendix Y. Polynomial byte representation and modular multiplication.
「Nielsen BookData」 より