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    • 暗能量/高瞻系列/中外物理学精品书系
      • 作者:李淼
      • 出版社:北京大学
      • ISBN:9787301210383
      • 出版日期:2012/08/01
      • 页数:267
    • 售价:26
  • 内容大纲

  • 作者介绍

        李淼,理论物理学家、畅销科普作家、文津图书奖得主。1982年毕业于北京大学天体物理专业,1984年获中国科技大学理学硕士学位。1989年赴丹麦哥本哈根大学玻尔研究所学习,1990年获哲学博士学位。1990年起先后在美国加州大学圣塔芭芭拉分校、布朗大学任研究助理教授,1996年在芝加哥大学费米研究所任高级研究助理。1999年回国,任中国科学院理论物理研究所研究员、博士生导师。2013年赴中山大学筹建天文与空间科学研究院并任院长。现为南方科技大学教授。身为大物理学家的李淼也活跃于科普领域,作品深受读者欢迎,屡获大奖。代表作有《给孩子讲量子力学》《给孩子讲宇宙》《给孩子讲相对论》《给孩子讲时间简史》《〈三体〉中的物理学》等。
  • 目录

    Part I Preliminaries in a Nutshell
    1 Gravitation.
      1.1 The Curved Spacetime
      1.2 The Curved Spacetime:an Example
      1.3 TheEinstein Equation
    2 Matter Components
      2. 1 The StressTensor
      2.2 Perfect Fluid
      2. 3 Observers and Energy Conditions
      2.4 TheVacuum
      2.5 Particles.
      2.6 Homogeneous Field Configurations
    3 Cosmology
      3.1 The Cosmological Principle
      3.2 Newtonian Cosmology
      3.3 FRW Cosmology
    Part II Theoretical Aspects
    4 Introduction to Dark Energy
      4.1 The Cosmological Constant Reloaded
      4.2 TheTheoretical ChallengeReferences  
    5 Weinberg's Classification
      5.1  Supersymmetry
      5.2  Anthropic Principle
      5.3  Tuning Mechanism
      5.4  Modifying Gravity
      5.5  Quantum Cosmology
      References
    6 Symmetry
      6.1  Supersymmetry in 2{1 Dimensions
      6.2  t HooftNobhenhuis Symmetry
      6.3  KaplanSundrum Symmetry
      6.4  Symmetry of Reversing Sign of the Metric
      6.5  Sealing Invariance in D > 4
      References
    7 Anthropic Principle
      7.1  BoussoPolchinski Scenario
      7.2  KKLT Scenario
      7.3  Populating the Landscape and Anthropic Interpretations.
    References
    8 Tuning Mechanisms
      8.1  Brane versus Bulk Mechanism
      8.2  Black Hole SelfAdjustment
    References
    9 Modified Gravity
      9.1  f(R) Models
      9.2  MOND and TeVeS Theories
      9.3  DGP Model
      9.4  Other Modified Gravity Theories
    References
    10  Quantum Cosmology

      10.1  Cosmological Constant Seesaw
      10.2  Wave Function through the Landscape
      References
    11  Holographic Principle
      11.1  The Holographic Principle
      11.2  Holographic Dark Energy
      11.3  Complementary Motivations
      11.4  Agegraphic Dark Energy
      11.5  Ricci Dark Energy
      References
    12  BackReaction
        12.1  SubHubble Inhomogeneities
        12.2  SuperHubble Inhomogeneities
        References
    13  Phenomenological Models
      13.1  Quintessence, Phantom and Quintom
      13.2  KEssense, Custuton, Braiding and Ghost Condensation
      13.3  Higher Spin Fields
      13.4  Chaplygin Gas and Viscous Fluid
      13.5  Particle Physics Models
      13.6  Dark Energy Perturbations
      References
    14  The Theoretical Challenge Revisited
      References
    Part III  Observational Aspects
    15  Basis of Statistics
      15.1  X2 Analysis
      15.2  Algorithms for the BestFit Analysis
      15.3  The Markov Chain Monte Carlo Algorithm
      15.4  The Fisher Matrix Techniques
      References
    16  Cosmic Probes of Dark Energy
      16.1  Type Ia Supernovae
      16.2  Cosmic Microwave Background
      16.3  Baryon Acoustic Oscillations
      16.4  Weak Lensing
      16.5  Galaxy Clusters
      16.6  GammaPay Burst
      16.7  XRay Observations
      16.8  Hubble Parameter Measurements
      16.9  Cosmic Age Tests
      16.10 Growth Factor
      16.11 Other Cosmological Probes
      References
    17  Dark Energy Projects
      17.1  OnGoing Projects
      17.2  IntermediateScale, NearFuture Projects
      17.3  LargerScale, LongerTerm Future Projects
      References
    18  Observational Constraints on Specific Theoretical Models

      18.1  Scalar Field Models
      18.2  Chaplygin Gas Models
      18.3  Holographic Dark Energy Models
      18.4  DvaliGabadadzePorrati Model
      18.5  f(R) Models
      18.6  Other Modified Gravity Models
      18.7  Inhomogeneous LTB and BackReartion Models
      18.8  Comparison of Dark Energy Models
      References
    19 Dark Energy Reconstructions from Observational Data
      19.1  Specific Ansatz
      19.2  Binned Parametrization
      19.3  Polynomial Fitting
      19.4  Gaussian Process Modeling
      References
    Index

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