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PRINCETON UNIVERSITY PRESS – The Physical Nature of Information 2025

Updated August 10, 2026 5.3 MB
PRINCETON UNIVERSITY PRESS – The Physical Nature of Information 2025

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Description

The Physical Nature of Information offers a new, physical approach to information theory, attempting to connect the abstract concepts of information with the fundamental laws of physics, particularly thermodynamics and statistical mechanics. By examining concepts such as entropy and free energy, the author shows how information acts as a physical entity in systems ranging from black holes to biological cells.

Designed for students and researchers who want to go beyond mere mathematical calculations to gain a deep understanding of the constraints imposed by uncertainty in the physical world, this work, written in a scientific yet concise language, provides the analytical tools needed for physicists, engineers, and even financial market analysts to look at problems in their fields from a new perspective.

Book Features

  • Providing a panoramic and comprehensive view of information theory from the perspective of physical sciences.
  • Exploring broad applications in diverse fields such as biology, economics, linguistics, and quantum computing.
  • Focus on the key concepts of Gibbs entropy and entanglement entropy as modern technical tools.
  • Explaining the relationship between knowledge (energy) and ignorance (entropy) in complex systems.
  • Suitable for short-term training courses with an emphasis on conceptual and combinatorial thinking.

Book specifications

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The Physical Nature of Information

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The Physical Nature of Information

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What is included

  • Providing a panoramic and comprehensive view of information theory from the perspective of physical sciences.
  • Exploring broad applications in diverse fields such as biology, economics, linguistics, and quantum computing.
  • Focus on the key concepts of Gibbs entropy and entanglement entropy as modern technical tools.
  • Explaining the relationship between knowledge (energy) and ignorance (entropy) in complex systems.
  • Suitable for short-term training courses with an emphasis on conceptual and combinatorial thinking.