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Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
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Entropy production in communication channels.

Farita Tasnim1, Nahuel Freitas2, David H Wolpert3

  • 1<a href="https://ror.org/042nb2s44">Massachusetts Institute of Technology</a>, Cambridge, 02139 Massachusetts, USA.

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Summary
This summary is machine-generated.

Complex systems often split information across multiple channels to reduce thermodynamic costs. This study provides the first physics-based evidence, using stochastic thermodynamics and information theory, that inverse multiplexing is efficient under certain conditions.

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Area of Science:

  • Complex Systems
  • Information Theory
  • Statistical Physics

Background:

  • Complex systems, both biological and artificial, incur significant thermodynamic costs for component communication.
  • Inverse multiplexing, splitting information across multiple channels, is hypothesized to reduce these costs.
  • A lack of physics-based theoretical frameworks for off-equilibrium systems has hindered validation.

Purpose of the Study:

  • To rigorously combine stochastic thermodynamics and Shannon information theory.
  • To investigate the relationship between thermodynamic costs and information capacity in communication systems.
  • To provide a physics-based understanding of inverse multiplexing strategies.

Main Methods:

  • Development of a minimal theoretical model for communication systems.
  • Integration of stochastic thermodynamics with Shannon information theory.
  • Analysis of entropy production in relation to channel capacity.

Main Results:

  • Entropy production is not universally convex or monotonically increasing with channel capacity.
  • These properties emerge for sufficiently high channel capacity.
  • The study challenges previous assumptions not grounded in first principles.

Conclusions:

  • Provides the first physics-based validation for inverse multiplexing strategies in reducing communication costs.
  • Defines the conditions under which splitting information across channels is thermodynamically favorable.
  • Offers a rigorous framework for analyzing information and thermodynamics in complex systems.