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经典与量子信息论(影印版)
  • 书号:9787030365101
    作者:(法)Emmanuel Desurvire
  • 外文书名:Classical and Quantum Information Theory
  • 装帧:平装
    开本:16
  • 页数:712
    字数:712
    语种:eng
  • 出版社:科学出版社
    出版时间:2013/3/14
  • 所属分类:
  • 定价: ¥158.00元
    售价: ¥124.82元
  • 图书介质:
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  • 购买数量: 件  可供
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  本书完整地叙述了经典信息论和量子信息论,首先介绍了香农熵的基本概念和各种应用,然后介绍了量子信息和量子计算的核心特点。本书从经典信息论和量子信息论的角度,介绍了编码、压缩、纠错、加密和信道容量等内容,采用非正式但科学的精确方法,为读者提供了理解量子门和电路的知识。   本书自始至终都在向读者介绍重要的结论,而不是让读者迷失在数学推导的细节中,并且配有大量的实践案例和章后习题,适合电子、通信、计算机等专业的研究生和科研人员学习参考。
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目录


  • Introduction

    1 Probability basics

    1.1 Events,event space,and probabilities

    1.2 Combinatorics

    1.3 Combined,joint,and conditional probabilities

    1.4 Exercises

    2 Probability distributions

    2.1 Mean and variance

    2.2 Exponential,Poisson,and binomial distributions

    2.3 Continuous distributions

    2.4 Uniform,exponential,and Gaussian(normal)distributions

    2.5 Central-limit theorem

    2.6 Exercises

    3 Measuring information

    3.1 Making sense of information

    3.2 Measuring information

    3.3 Information bits

    3.4 Rényi?s fake coin

    3.5 Exercises

    4 Entropy

    4.1 From Boltzmann to Shannon

    4.2 Entropy in dice

    4.3 Language entropy

    4.4 Maximum entropy(discrete source)

    4.5 Exercises

    5 Mutual information and more entropies

    5.1 Joint and conditional entropies

    5.2 Mutual information

    5.3 Relative entropy

    5.4 Exercises

    6 Differential entropy

    6.1 Entropy of continuous sources

    6.2 Maximum entropy(continuous source)

    6.3 Exercises

    7 Algorithmic entropy and Kolmogorov complexity

    7.1 Defining algorithmic entropy

    7.2 The Turing machine

    7.3 Universal Turing machine

    7.4 Kolmogorov complexity

    7.5 Kolmogorov complexity vs. Shannon?s entropy

    7.6 Exercises

    8 Information coding

    8.1 Coding numbers

    8.2 Coding language

    8.3 The Morse code

    8.4 Mean code length and coding efficiency

    8.5 Optimizing coding efficiency

    8.6 Shannon?s source-coding theorem

    8.7 Exercises

    9 Optimal coding and compression

    9.1 Huffman codes

    9.2 Data compression

    9.3 Block codes

    9.4 Exercises

    10 Integer,arithmetic,and adaptive coding

    10.1 Integer coding

    10.2 Arithmetic coding

    10.3 Adaptive Huffman coding

    10.4 Lempel-Ziv coding

    10.5 Exercises

    11 Error correction

    11.1 Communication channel

    11.2 Linear block codes

    11.3 Cyclic codes

    11.4 Error-correction code types

    11.5 Corrected bit-error-rate

    11.6 Exercises

    12 Channel entropy

    12.1 Binary symmetric channel

    12.2 Nonbinary and asymmetric discrete channels

    12.3 Channel entropy and mutual information

    12.4 Symbol error rate

    12.5 Exercises

    13 Channel capacity and coding theorem

    13.1 Channel capacity

    13.2 Typical sequences and the typical set

    13.3 Shannon?s channel coding theorem

    13.4 Exercises

    14 Gaussian channel and Shannon-Hartley theorem

    14.1 Gaussian channel

    14.2 Nonlinear channel

    14.3 Exercises

    15 Reversible computation

    15.1 Maxwell?s demon and Landauer?s principle

    15.2 From computer architecture to logic gates

    15.3 Reversible logic gates and computation

    15.4 Exercises

    16 Quantum bits and quantum gates

    16.1 Quantum bits

    16.2 Basic computations with 1-qubit quantum gates

    16.3 Quantum gates with multiple qubit inputs and outputs

    16.4 Quantum circuits

    16.5 Tensor products

    16.6 Noncloning theorem

    16.7 Exercises

    17 Quantum measurements

    17.1 Dirac notation

    17.2 Quantum measurements and types

    17.3 Quantum measurements on joint states

    17.4 Exercises

    18 Qubit measurements,superdense coding,and quantum teleportation

    18.1 Measuring single qubits

    18.2 Measuring n-qubits

    18.3 Bell state measurement

    18.4 Superdense coding

    18.5 Quantum teleportation

    18.6 Distributed quantum computing

    18.7 Exercises

    19 Deutsch-Jozsa,quantum Fourier transform,and Grover quantum database search algorithms

    19.1 Deutsch algorithm

    19.2 Deutsch-Jozsa algorithm

    19.3 Quantum Fourier transform algorithm

    19.4 Grover quantum database search algorithm

    19.5 Exercises

    20 Shor?s factorization algorithm

    20.1 Phase estimation

    20.2 Order finding

    20.3 Continued fraction expansion

    20.4 From order finding to factorization

    20.5 Shor?s factorization algorithm

    20.6 Factorizing N=15 and other nontrivial composites

    20.7 Public-key cryptography

    20.8 Exercises

    21 Quantum information theory

    21.1 Von Neumann entropy

    21.2 Relative,joint,and conditional entropy,and mutual information

    21.3 Quantum communication channel and Holevo bound

    21.4 Exercises

    22 Quantum data compression

    22.1 Quantum data compression and fidelity

    22.2 Schumacher?s quantum coding theorem

    22.3 A graphical and numerical illustration of Schumacher?s quantum coding theorem

    22.4 Exercises

    23 Quantum channel noise and channel capacity

    23.1 Noisy quantum channels

    23.2 The Holevo-Schumacher-Westmoreland capacity theorem

    23.3 Capacity of some quantum channels

    23.4 Exercises

    24 Quantum error correction

    24.1 Quantum repetition code

    24.2 Shor code

    24.3 Calderbank-Shor-Steine(CSS)codes

    24.4 Hadamard-Steane code

    24.5 Exercises

    25 Classical and quantum cryptography

    25.1 Message encryption,decryption,and code breaking

    25.2 Encryption and decryption with binary numbers

    25.3 Double-key encryption

    25.4 Cryptography without key exchange

    25.5 Public-key cryptography and RSA

    25.6 Data encryption standard(DES)and advanced encryption standard(AES)

    25.7 Quantum cryptography

    25.8 Electromagnetic waves,polarization states,photons,and quantum measurements

    25.9 A secure photon communication channel

    25.10 The BB84 protocol for QKD

    25.11 The B92 protocol

    25.12 The EPR protocol

    25.13 Is quantum cryptography?invulnerable??

    Appendix A(Chapter 4)Boltzmann’s entropy

    Appendix B(Chapter 4)Shannon’s entropy

    Appendix C(Chapter 4)Maximum entropy of discrete sources

    Appendix D(Chapter 5)Markov chains and the second law of thermodynamics

    Appendix E(Chapter 6)From discrete to continuous entropy

    Appendix F(Chapter 8)Kraft-McMillan inequality

    Appendix G(Chapter 9)Overview of data compression standards

    Appendix H(Chapter 10)Arithmetic coding algorithm

    Appendix I(Chapter 10)Lempel-Ziv distinct parsing

    Appendix J(Chapter 11)Error-correction capability of linear block codes

    Appendix K(Chapter 13)Capacity of binary communication channels

    Appendix L(Chapter 13)Converse proof of the channel coding theorem

    Appendix M(Chapter 16)Bloch sphere representation of the qubit

    Appendix N(Chapter 16)Pauli matrices,rotations,and unitary operators

    Appendix O(Chapter 17)Heisenberg uncertainty principle

    Appendix P(Chapter 18)Two-qubit teleportation

    Appendix Q(Chapter 19)Quantum Fourier transform circuit

    Appendix R(Chapter 20)Properties of continued fraction expansion

    Appendix S(Chapter 20)Computation of inverse Fourier transform in the factorization of N=21 through Shor’s algorithm

    Appendix T(Chapter 20)Modular arithmetic and Euler’s theorem

    Appendix U(Chapter 21)Klein’s inequality

    Appendix V(Chapter 21)Schmidt decomposition of joint pure states

    Appendix W(Chapter 21)State purification

    Appendix X(Chapter 21)Holevo bound

    Appendix Y(Chapter 25)Polynomial byte representation and modular multiplication

    Index]]>
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