Abstract
Using the problem of ion channel thermodynamics as an example, we illustrate the idea of building up complex thermodynamic models by successively adding physical information. We present a new formulation of information algebra that generalizes methods of both information theory and statistical mechanics. From this foundation we derive a theory for ion channel kinetics, identifying a nonequilibrium 'process' free energy functional in addition to the well-known integrated work functionals. The Gibbs-Maxwell relation for the free energy functional is a Green-Kubo relation, applicable arbitrarily far from equilibrium, that captures the effect of non-local and time-dependent behavior from transient thermal and mechanical driving forces. Comparing the physical significance of the Lagrange multipliers to the canonical ensemble suggests definitions of nonequilibrium ensembles at constant capacitance or inductance in addition to constant resistance. Our result is that statistical mechanical descriptions derived from a few primitive algebraic operations on information can be used to create experimentally-relevant and computable models. By construction, these models may use information from more detailed atomistic simulations. Two surprising consequences to be explored in further work are that (in)distinguishability factors are automatically predicted from the problem formulation and that a direct analogue of the second law for thermodynamic entropy production is found by considering information loss in stochastic processes. The information loss identifies a novel contribution from the instantaneous information entropy that ensures non-negative loss.
Original language | English |
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Pages (from-to) | 385-409 |
Number of pages | 25 |
Journal | Journal of Statistical Physics |
Volume | 145 |
Issue number | 2 |
DOIs | |
State | Published - Oct 2011 |
Externally published | Yes |
Funding
Acknowledgements This work was supported, in part, by Sandia’s LDRD program, and, in part, by the National Institutes of Health through the NIH Road Map for Medical Research. TLB gratefully acknowledges the support of NSF grants CHE-0709560 and CHE-1011746. Sandia National Laboratories is a multi-program laboratory operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000.
Funders | Funder number |
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Sandia’s LDRD | |
National Science Foundation | CHE-1011746, CHE-0709560 |
National Science Foundation | |
National Institutes of Health |
Keywords
- Information entropy
- Likelihood
- Maximum entropy
- Predictive statistical mechanics
- Probability