Information Geometry of Non-Equilibrium Processes in a Bistable System with a Cubic Damping

A probabilistic description is essential for understanding the dynamics of stochastic systems far from equilibrium, given uncertainty inherent in the systems. To compare different Probability Density Functions (PDFs), it is extremely useful to quantify the difference among different PDFs by assigning an appropriate metric to probability such that the distance increases with the difference between the two PDFs. This metric structure then provides a key link between stochastic systems and information geometry. For a non-equilibrium process, we define an infinitesimal distance at any time by comparing two PDFs at times infinitesimally apart and sum these distances in time. The total distance along the trajectory of the system quantifies the total number of different states that the system undergoes in time and is called the information length. By using this concept, we investigate the information geometry of non-equilibrium processes involved in disorder-order transitions between the critical and subcritical states in a bistable system. Specifically, we compute time-dependent PDFs, information length, the rate of change in information length, entropy change and Fisher information in disorder-to-order and order-to-disorder transitions and discuss similarities and disparities between the two transitions. In particular, we show that the total information length in order-to-disorder transition is much larger than that in disorder-to-order transition and elucidate the link to the drastically different evolution of entropy in both transitions. We also provide the comparison of the results with those in the case of the transition between the subcritical and supercritical states and discuss implications for fitness.

[1]  M. A. Muñoz,et al.  Stochastic Amplification of Fluctuations in Cortical Up-States , 2012, PloS one.

[2]  Rainer Hollerbach,et al.  Signature of nonlinear damping in geometric structure of a nonequilibrium process. , 2017, Physical review. E.

[3]  K. Sayanagi,et al.  The Emergence of Multiple Robust Zonal Jets from Freely Evolving, Three-Dimensional Stratified Geostrophic Turbulence with Applications to Jupiter , 2008 .

[4]  Hilbert J. Kappen,et al.  Irregular Dynamics in Up and Down Cortical States , 2010, PloS one.

[5]  F. Schlögl,et al.  Thermodynamic metric and stochastic measures , 1985 .

[6]  G. Ruppeiner,et al.  Thermodynamics: A Riemannian geometric model , 1979 .

[7]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[8]  Peter Salamon,et al.  A Simple Example of Control to Minimize Entropy Production , 2002 .

[9]  Henrik Jeldtoft Jensen,et al.  Self-Organized Criticality: Emergent Complex Behavior in Physical and Biological Systems , 1998 .

[10]  R. Kubo,et al.  Fluctuation and relaxation of macrovariables , 1973 .

[11]  Alison L Gibbs,et al.  On Choosing and Bounding Probability Metrics , 2002, math/0209021.

[12]  M. Suzuki,et al.  Theory of instability, nonlinear brownian motion and formation of macroscopic order , 1978 .

[13]  Eun-Jin Kim,et al.  Structures in Sound: Analysis of Classical Music Using the Information Length , 2016, Entropy.

[14]  A. Lesne,et al.  Self-Organised Criticality , 2012 .

[15]  Jonathan M. Nichols,et al.  Calculation of Differential Entropy for a Mixed Gaussian Distribution , 2008, Entropy.

[16]  Peter H. Richter Information and Self-organization: A Macroscopic Approach to Complex Systems, Hermann Haken. Springer, New York (1988), $59.50 (cloth), 196 pp , 1991 .

[17]  J. Elgin The Fokker-Planck Equation: Methods of Solution and Applications , 1984 .

[18]  Kaushik Srinivasan,et al.  Zonostrophic Instability , 2011 .

[19]  Eduardo Sontag,et al.  Untangling the wires: A strategy to trace functional interactions in signaling and gene networks , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[20]  T. Kibble,et al.  Some Implications of a Cosmological Phase Transition , 1980 .

[21]  Geometric structure and information change in phase transitions. , 2017, Physical review. E.

[22]  James Heseltine,et al.  Geometric structure and geodesic in a solvable model of nonequilibrium process. , 2016, Physical review. E.

[23]  R. Bogacz,et al.  Progress in Biophysics and Molecular Biology , 2010 .

[24]  Anja Walter,et al.  Introduction To Stochastic Calculus With Applications , 2016 .

[25]  Sanjay Tyagi Tuning noise in gene expression , 2015, Molecular Systems Biology.

[26]  Gavin E Crooks,et al.  Measuring thermodynamic length. , 2007, Physical review letters.

[27]  Terry Bossomaier,et al.  Information and phase transitions in socio-economic systems , 2013, Complex Adapt. Syst. Model..

[28]  G. Longo,et al.  From physics to biology by extending criticality and symmetry breakings. , 2011, Progress in biophysics and molecular biology.

[29]  W. Wootters Statistical distance and Hilbert space , 1981 .

[30]  M. A. Muñoz,et al.  Self-Organized Bistability Associated with First-Order Phase Transitions. , 2016, Physical review letters.

[31]  Han L. Liu,et al.  On the self-organizing process of large scale shear flows , 2013 .

[32]  James Heseltine,et al.  Novel mapping in non-equilibrium stochastic processes , 2016 .

[33]  S. Fauve,et al.  Stochastic resonance in a bistable system , 1983 .

[34]  Augusto Smerzi,et al.  Fisher information and entanglement of non-Gaussian spin states , 2014, Science.

[35]  Per Bak,et al.  Mean field theory of self-organized critical phenomena , 1988 .

[36]  Gavin E Crooks,et al.  Far-from-equilibrium measurements of thermodynamic length. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[37]  Bjarne Andresen,et al.  Quasistatic processes as step equilibrations , 1985 .

[38]  A. Giuliani,et al.  Emergent Self-Organized Criticality in Gene Expression Dynamics: Temporal Development of Global Phase Transition Revealed in a Cancer Cell Line , 2015, PloS one.

[39]  Ovidiu Radulescu,et al.  Reconciling molecular regulatory mechanisms with noise patterns of bacterial metabolic promoters in induced and repressed states , 2011, Proceedings of the National Academy of Sciences.

[40]  Y. Nagashima Elementary Particle Physics: Quantum Field Theory and Particles , 2010 .

[41]  Rainer Hollerbach,et al.  Time-dependent probability density function in cubic stochastic processes. , 2016, Physical review. E.

[42]  Eun-jin Kim Consistent theory of turbulent transport in two-dimensional magnetohydrodynamics. , 2006, Physical review letters.

[43]  Theory of unstable growth. , 1994, Physical review. B, Condensed matter.

[44]  P. Diamond,et al.  Zonal flows and transient dynamics of the L-H transition. , 2003, Physical review letters.

[45]  S. Nicholson,et al.  Investigation of the statistical distance to reach stationary distributions , 2015 .

[46]  S. Braunstein,et al.  Statistical distance and the geometry of quantum states. , 1994, Physical review letters.

[47]  David A. Sivak,et al.  Thermodynamic metrics and optimal paths. , 2012, Physical review letters.

[48]  U. Sauer,et al.  Multidimensional Optimality of Microbial Metabolism , 2012, Science.

[49]  Misha Tsodyks,et al.  The Emergence of Up and Down States in Cortical Networks , 2006, PLoS Comput. Biol..

[50]  Masuo Suzuki Scaling theory of transient phenomena near the instability point , 1977 .

[51]  C. Caroli,et al.  Diffusion in a bistable potential: A systematic WKB treatment , 1979 .