Intrinsic Information Processing and Energy Dissipation in Stochastic Input-Output Dynamical Systems

Abstract

Recent theoretical and experimental advances in nonequilibrium thermodynamics provide a new understanding of how intelligent control can convert information to energy. However, these approaches have yet to account for the diverse kinds of information that complex nonlinear systems are capable of producing and storing. This is particularly a concern regarding the diversity of differently structured irreversible processes, which play key role in limiting computation. Fortunately, computational mechanics accounts for this diversity, but in autonomous dynamical systems. Thermodynamic cycles that perform useful information processing are nonautonomous systems. To analyze information processing in nonautonomous systems, computational mechanics must be ex- tended to controlled dynamical systems. Additionally, it must be augmented to account for the energetics that support information generation and storage.

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Document Details

Document Type
Technical Report
Publication Date
Jul 09, 2015
Accession Number
ADA624810

Entities

People

  • James P. Crutchfield

Organizations

  • University of California

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Complex Systems
  • Computational Science
  • Computer Science
  • Computers
  • High Performance Computing
  • Information Processing
  • Information Theory
  • Machine Learning
  • Materials
  • Neural Networks
  • Nonlinear Systems
  • Statistical Mechanics
  • Stochastic Processes
  • Students
  • Thermodynamics

Readers

  • Calculus or Mathematical Analysis
  • Computational Fluid Dynamics (CFD)
  • Systems Analysis and Design