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The Physical Nature of Information

A Short Course

Gregory Falkovich

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Princeton University Press img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Informatik, EDV

Beschreibung

A unified introduction to information theory for scientists

Applications of information theory span a broad range of disciplines today. This book presents a unified treatment of the subject for students and practitioners in the sciences. It teaches the tools universally used by physicists working on quantum computers and black holes, engineers designing self-driving cars, traders perfecting market strategies, chemists playing with molecules, biologists studying cells and living beings, linguists analyzing languages, and neuroscientists figuring out how the brain works. No matter what area of science you specialize in, The Physical Nature of Information unlocks the power of information theory to test the limits imposed by uncertainty.

  • Provides a panoramic approach to information theory
  • Draws on examples from physics, engineering, biology, economics, and linguistics
  • Applications range from thermodynamics and statistical mechanics to dynamical chaos, information and communication theories, and quantum information
  • Includes materials for lectures and tutorials along with exercises with detailed solutions
  • Can be used to design a one-semester introductory course
  • Ideal for self-study by graduate students and advanced undergraduates
  • Invaluable for scholars seeking new research opportunities

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Schlagwörter

Hypothesis, Bits, Length, Gibbs, Data, Orthogonal, Law, Degrees freedom, Evolution, Encode, Product, Density, Scale, Brain, Hamiltonian, Maximal, Momentum, Distribution, Momenta, Dimensional, Equation, Positive, Factor, Direction, Line, Points, Degrees, Physics, Distortion, Respect, Correlations, Density matrix, Parameters, Matrix, Microcanonical, Analog, Entropy, Energy, Particle, Quantum, Constant, Alphabet, Entanglement, Operator, Information, Chain, Input, Freedom, Quantities, Heat, Knowledge, Growth, Letter, Qubit, Equilibrium, Relative, Conditional probability, Binary, Flow, Choice, Force, Function, Result, Alice, Gaussian, Logarithm, Output, Sensory, Boltzmann, Neumann