经典与量子信息论（英文版）

　　Foreword
　　Introduction
　　1 Probability basics
　　1.1 Events, event space, and probabilities
　　1.2 Combinatorics
　　1.3 Combined, joint, and conditional probabilities
　　1.4 Exercises2 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 Exercises3 Measuring information
　　3.1 Making sense of information
　　3.2 Measuring information
　　3.3 Information bits
　　3.4 Renyi's fake coin
　　3.5 Exercises4 Entropy
　　4.1 From Boltzmann to Shannon
　　4.2 Entropy in dice
　　4.3 Language entropy
　　4.4 Maximum entropy (discrete source)
　　4.5 Exercises5 Mutual information and more entropies
　　5.1 Joint and conditional entropies
　　5.2 Mutual information
　　5.3 Relative entropy
　　5.4 Exercises6 Differential entropy
　　6.1 Entropy of continuous sources
　　6.2 Maximum entropy (continuous source)
　　6.3 Exercises7 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 Exercises8 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 Exercises9 Optimal coding and compression
　　9.1 Huffman codes
　　9.2 Data compression
　　9.3 Block codes
　　9.4 Exercises10 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 Exercises11 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 Exercises12 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 Exercises13 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 Exercises14 Gaussian channel and Shannon-Hartley theorem
　　14.1 Gaussian channel
　　14.2 Nonlinear channel
　　14.3 Exercises15 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 Exercises16 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 Exercises17 Quantum measurements
　　17.1 Dirac notation
　　17.2 Quantum measurements and types
　　17.3 Quantum measurements on joint states
　　17.4 Exercises18 Qubit measurements, superdense coding, and quantum teleportaUon
　　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 Exercises19 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 Exercises20 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 Exercises21 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
　　……
　　25 Classical and quantum cryptography

　　《经典与量子信息论（英文版）》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r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。