The Free Energy Requirements of Biological Organisms; Implications for Evolution

Recent advances in nonequilibrium statistical physics have provided unprecedented insight into the thermodynamics of dynamic processes. The author recently used these advances to extend Landauer's semi-formal reasoning concerning the thermodynamics of bit erasure, to derive the minimal free energy required to implement an arbitrary computation. Here, I extend this analysis, deriving the minimal free energy required by an organism to run a given (stochastic) map $\pi$ from its sensor inputs to its actuator outputs. I use this result to calculate the input-output map $\pi$ of an organism that optimally trades off the free energy needed to run $\pi$ with the phenotypic fitness that results from implementing $\pi$. I end with a general discussion of the limits imposed on the rate of the terrestrial biosphere's information processing by the flux of sunlight on the Earth.

[1]  David J. C. MacKay,et al.  Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.

[2]  Charles H. Bennett,et al.  Notes on Landauer's Principle, Reversible Computation, and Maxwell's Demon , 2002, physics/0210005.

[3]  S. Laughlin Energy as a constraint on the coding and processing of sensory information , 2001, Current Opinion in Neurobiology.

[4]  Dean J. Driebe,et al.  Generalization of the second law for a transition between nonequilibrium states , 2010 .

[5]  T. Toffoli,et al.  Conservative logic , 2002, Collision-Based Computing.

[6]  Christopher Jarzynski,et al.  Work and information processing in a solvable model of Maxwell’s demon , 2012, Proceedings of the National Academy of Sciences.

[7]  F. Moukalled,et al.  A Simple Derivation of Crooks Relation , 2013 .

[8]  David H. Wolpert,et al.  Extending Landauer's Bound from Bit Erasure to Arbitrary Computation , 2015, 1508.05319.

[9]  David J. Schwab,et al.  Landauer in the Age of Synthetic Biology: Energy Consumption and Information Processing in Biochemical Networks , 2015, bioRxiv.

[10]  Masahito Ueda,et al.  Minimal energy cost for thermodynamic information processing: measurement and information erasure. , 2008, Physical review letters.

[11]  Jordan M. Horowitz,et al.  Thermodynamic Costs of Information Processing in Sensory Adaptation , 2014, PLoS Comput. Biol..

[12]  S. Frank Natural selection maximizes Fisher information , 2009, Journal of evolutionary biology.

[13]  S. Leibler,et al.  Phenotypic Diversity, Population Growth, and Information in Fluctuating Environments , 2005, Science.

[14]  M. B. Plenio,et al.  The physics of forgetting: Landauer's erasure principle and information theory , 2001, quant-ph/0103108.

[15]  Pieter Rein Ten Wolde,et al.  Optimal resource allocation in cellular sensing systems , 2014, Proceedings of the National Academy of Sciences.

[16]  S. Frank Natural selection. V. How to read the fundamental equations of evolutionary change in terms of information theory , 2012, Journal of evolutionary biology.

[17]  Carl T. Bergstrom,et al.  The fitness value of information , 2005, Oikos.

[18]  Blake S. Pollard A Second Law for Open Markov Processes , 2016, Open Syst. Inf. Dyn..

[19]  David J Schwab,et al.  Energetic costs of cellular computation , 2012, Proceedings of the National Academy of Sciences.

[20]  Charles S. Cockell,et al.  An Estimate of the Total DNA in the Biosphere , 2015, PLoS biology.

[21]  Charles H. Bennett,et al.  The thermodynamics of computation—a review , 1982 .

[22]  Mikhail Prokopenko,et al.  Information thermodynamics of near-equilibrium computation. , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.

[23]  Raymond W. Yeung,et al.  A First Course in Information Theory , 2002 .

[24]  G. Crooks Entropy production fluctuation theorem and the nonequilibrium work relation for free energy differences. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[25]  R. Landauer The physical nature of information , 1996 .

[26]  O. Maroney Generalizing Landauer's principle. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[27]  H. Hasegawa,et al.  Generalization of the Second Law for a Nonequilibrium Initial State , 2009, 0907.1569.

[28]  Charles H. Bennett,et al.  Logical reversibility of computation , 1973 .

[29]  M. Esposito,et al.  Three faces of the second law. I. Master equation formulation. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[30]  Charles H. Bennett Time/Space Trade-Offs for Reversible Computation , 1989, SIAM J. Comput..

[31]  Anders Sandberg Energetics of the brain and AI , 2016, ArXiv.

[32]  G. Vinnicombe,et al.  Fundamental limits on the suppression of molecular fluctuations , 2010, Nature.

[33]  F. Reif,et al.  Fundamentals of Statistical and Thermal Physics , 1965 .

[34]  Jeremy L. England,et al.  Statistical physics of self-replication. , 2012, The Journal of chemical physics.

[35]  Rolf Landauer,et al.  Minimal Energy Requirements in Communication , 1996, Science.

[36]  Paul M. B. Vitányi,et al.  Shannon Information and Kolmogorov Complexity , 2004, ArXiv.

[37]  D. Krakauer Darwinian demons, evolutionary complexity, and information maximization. , 2011, Chaos.

[38]  Shizume Heat generation required by information erasure. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[39]  C. Jarzynski Nonequilibrium Equality for Free Energy Differences , 1996, cond-mat/9610209.

[40]  U. Seifert Stochastic thermodynamics, fluctuation theorems and molecular machines , 2012, Reports on progress in physics. Physical Society.

[41]  Udo Seifert,et al.  Stochastic thermodynamics with information reservoirs. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[42]  Eric Lutz,et al.  Comment on "Minimal energy cost for thermodynamic information processing: measurement and information erasure". , 2010, Physical review letters.

[43]  Massimiliano Esposito,et al.  Second law and Landauer principle far from equilibrium , 2011, 1104.5165.

[44]  C. Jarzynski,et al.  Information Processing and the Second Law of Thermodynamics: An Inclusive Hamiltonian Approach. , 2013, 1308.5001.

[45]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[46]  Susanne Still,et al.  The thermodynamics of prediction , 2012, Physical review letters.

[47]  Pieter Rein ten Wolde,et al.  Energy dissipation and noise correlations in biochemical sensing. , 2014, Physical review letters.

[48]  S. F. Taylor,et al.  Information and fitness , 2007, 0712.4382.

[49]  R. Landauer,et al.  Irreversibility and heat generation in the computing process , 1961, IBM J. Res. Dev..

[50]  Ming Li,et al.  An Introduction to Kolmogorov Complexity and Its Applications , 2019, Texts in Computer Science.

[51]  Udo Seifert,et al.  An autonomous and reversible Maxwell's demon , 2013 .

[52]  Seth Lloyd,et al.  Information-theoretic approach to the study of control systems , 2001, physics/0104007.

[53]  G. Crooks Nonequilibrium Measurements of Free Energy Differences for Microscopically Reversible Markovian Systems , 1998 .

[54]  T. Sagawa Thermodynamic and logical reversibilities revisited , 2013, 1311.1886.

[55]  M. N. Bera,et al.  Thermodynamics from Information , 2018, 1805.10282.

[56]  Masahito Ueda,et al.  Fluctuation theorem with information exchange: role of correlations in stochastic thermodynamics. , 2012, Physical review letters.

[57]  O. Sporns,et al.  The economy of brain network organization , 2012, Nature Reviews Neuroscience.