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When Maxwell's Demon leaves the room.

P G Tello1, S Kauffman2

  • 1CERN, Geneva, Switzerland.

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|October 16, 2025
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Summary
This summary is machine-generated.

This study reinterprets the Maxwell Demon to show how physical laws and random fluctuations, not intentional agents, drive evolutionary order. Information theory models reveal how these processes decrease entropy and generate complexity, highlighting exaptations in evolution.

Keywords:
DissipationEntropyInformationMaxwell Demon

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Area of Science:

  • Physics
  • Information Theory
  • Evolutionary Biology

Background:

  • The Maxwell Demon thought experiment traditionally involves an intelligent agent reducing entropy.
  • Understanding the emergence of order in biological systems without invoking purposeful agency remains a challenge.

Purpose of the Study:

  • To re-examine the Maxwell Demon paradigm from an information-theoretic viewpoint.
  • To explore how physical laws and stochastic processes can naturally generate order and complexity.
  • To investigate the role of information, memory, and correlation in evolutionary dynamics.

Main Methods:

  • Utilized information-theoretic models, including binary and Z-channels.
  • Analyzed the effects of random fluctuations, such as stochastic resonance.
  • Investigated emergent properties like non-ergodicity, mutual information, and entropy reduction.

Main Results:

  • Demonstrated that random fluctuations can decrease entropy and generate mutual information.
  • Showed that order can emerge from physical laws and stochastic processes without intentional agents.
  • Identified memory and correlation as emergent features of physical interactions.

Conclusions:

  • Reinterpreted evolutionary order as a natural outcome of physical laws and stochasticity.
  • Highlighted the significance of exaptations over adaptations in driving biological evolution.
  • Emphasized the relevance of information-theoretic concepts for understanding purposeless evolutionary dynamics.