Hidden Markov models for stochastic thermodynamics

The formalism of state estimation and hidden Markov models can simplify and clarify the discussion of stochastic thermodynamics in the presence of feedback and measurement errors. After reviewing the basic formalism, we use it to shed light on a recent discussion of phase transitions in the optimize...

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Bibliographic Details
Published in:New journal of physics 2015-07, Vol.17 (7), p.75003
Main Author: Bechhoefer, John
Format: Article
Language:English
Subjects:
Control theory
Displays
Engine noise
Feedback
Formalism
hidden Markov models
Information flow
information theory
Markov analysis
Markov chains
Mathematical models
Noise control
Noise measurement
nonequilibrium thermodynamics
Phase transitions
Physics
State estimation
Stochasticity
Thermodynamics
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Summary:The formalism of state estimation and hidden Markov models can simplify and clarify the discussion of stochastic thermodynamics in the presence of feedback and measurement errors. After reviewing the basic formalism, we use it to shed light on a recent discussion of phase transitions in the optimized response of an information engine, for which measurement noise serves as a control parameter. The HMM formalism also shows that the value of additional information displays a maximum at intermediate signal-to-noise ratios. Finally, we discuss how systems open to information flow can apparently violate causality; the HMM formalism can quantify the performance gains due to such violations.
ISSN:1367-2630
1367-2630
DOI:10.1088/1367-2630/17/7/075003