Information-theoretic vs. thermodynamic entropy production in autonomous sensory networks

Abstract

For sensory networks, we determine the rate with which they acquire information about the changing external conditions. Comparing this rate with the thermodynamic entropy production that quantifies the cost of maintaining the network, we find that there is no universal bound restricting the rate of obtaining information to be less than this thermodynamic cost. These results are obtained within a general bipartite model consisting of a stochastically changing environment that affects the instantaneous transition rates within the system. Moreover, they are illustrated with a simple four-states model motivated by cellular sensing. On the technical level, we obtain an upper bound on the rate of mutual information analytically and calculate this rate with a numerical method that estimates the entropy of a time-series generated with a simulation.

6 pages, 4 figures

References in corpus (4)

• The Physics of Maxwell's demon and information
• Work and information processing in a solvable model of Maxwell's demon
• Thermodynamics of feedback controlled systems
• Stochastic thermodynamics for "Maxwell demon" feedbacks

Cited by in corpus (9)

• Thermodynamic uncertainty relation for biomolecular processes
• Thermodynamic costs of information processing in sensory adaption
• Efficiency of cellular information processing
• Cost and Precision of Brownian Clocks
• Fluctuation Theorem for Partially-masked Nonequilibrium Dynamics
• Second-law-like inequalities with information and their interpretations
• Thermodynamics of statistical inference by cells
• Nonequilibrium sensing and its analogy to kinetic proofreading
• Application of Mutual Information Methods in Time-Distance Helioseismology