4.4 Article

Leveraging Environmental Correlations: The Thermodynamics of Requisite Variety

Journal

JOURNAL OF STATISTICAL PHYSICS
Volume 167, Issue 6, Pages 1555-1585

Publisher

SPRINGER
DOI: 10.1007/s10955-017-1776-0

Keywords

Maxwell's Demon; Cybernetics; Detailed balance; Entropy rate; Second Law of Thermodynamics; Transducer; Adaptation

Funding

  1. FQXi Grant [FQXi-RFP-1609]
  2. U. S. Army Research Office [W911NF-13-1-0390, W911NF12-1-0234]
  3. U. S. Army Research Laboratory

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Key to biological success, the requisite variety that confronts an adaptive organism is the set of detectable, accessible, and controllable states in its environment. We analyze its role in the thermodynamic functioning of information ratchets-a form of autonomous Maxwellian Demon capable of exploiting fluctuations in an external information reservoir to harvest useful work from a thermal bath. This establishes a quantitative paradigm for understanding how adaptive agents leverage structured thermal environments for their own thermodynamic benefit. General ratchets behave as memoryful communication channels, interacting with their environment sequentially and storing results to an output. The bulk of thermal ratchets analyzed to date, however, assume memoryless environments that generate input signals without temporal correlations. Employing computational mechanics and a new information-processing Second Law of Thermodynamics (IPSL) we remove these restrictions, analyzing general finite-state ratchets interacting with structured environments that generate correlated input signals. On the one hand, we demonstrate that a ratchet need not have memory to exploit an uncorrelated environment. On the other, and more appropriate to biological adaptation, we show that a ratchet must have memory to most effectively leverage structure and correlation in its environment. The lesson is that to optimally harvest work a ratchet's memory must reflect the input generator's memory. Finally, we investigate achieving the IPSL bounds on the amount of work a ratchet can extract from its environment, discovering that finite-state, optimal ratchets are unable to reach these bounds. In contrast, we show that infinite-state ratchets can go well beyond these bounds by utilizing their own infinite negentropy. We conclude with an outline of the collective thermodynamics of information-ratchet swarms.

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