Thermodynamics of Isothermal Brownian Motors

Parrondo, Juan M. R.; Cisneros, B. Jiménez de; Brito, Ricardo

doi:10.1007/3-540-45396-2_4

Cited by 10 publications

(5 citation statements)

References 8 publications

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“…Otherwise she tosses the good coin and wins with probability p g = 3/4 − ǫ. It can be shown [22] that these rules make B also a losing game in the long run. The paradox arises when alternating game A and B either in a random or periodic fashion, as this yields an average capital that increases with t, provided ǫ is small enough.…”

Section: The Gamesmentioning

confidence: 99%

Optimal sequence for Parrondo games

Dinís

2008

Phys. Rev. E

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An algorithm based on backward induction is devised in order to compute the optimal sequence of games to be played in Parrondo games. The algorithm can be used to find the optimal sequence for any finite number of turns or in the steady state, showing that ABABB... is the sequence with the highest steady state average gain. The algorithm can also be generalized to find the optimal adaptive strategy in a multiplayer version of the games, where a finite number of players may choose, at every turn, the game the whole ensemble should play.

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Section: The Gamesmentioning

confidence: 99%

Optimal sequence for Parrondo games

Dinís

2008

Phys. Rev. E

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“…To relate the statistical measures in Section 4.1 to thermodynamics, we let U (internal energy) be the average potential energy U = V and obtain (see also [66,113] and references therein)…”

Section: Non-equilibrium Thermodynamical Lawsmentioning

confidence: 99%

“…To this end, let us first define the microscopic free energy µ = V + D ln p (called the chemical potential energy in [113]). In terms of µ, we have J = −p∂ x µ and µ = U − DS = F .…”

Section: Inequalitiesmentioning

confidence: 99%

Information Geometry, Fluctuations, Non-Equilibrium Thermodynamics, and Geodesics in Complex Systems

Kim

2021

Entropy

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Information theory provides an interdisciplinary method to understand important phenomena in many research fields ranging from astrophysical and laboratory fluids/plasmas to biological systems. In particular, information geometric theory enables us to envision the evolution of non-equilibrium processes in terms of a (dimensionless) distance by quantifying how information unfolds over time as a probability density function (PDF) evolves in time. Here, we discuss some recent developments in information geometric theory focusing on time-dependent dynamic aspects of non-equilibrium processes (e.g., time-varying mean value, time-varying variance, or temperature, etc.) and their thermodynamic and physical/biological implications. We compare different distances between two given PDFs and highlight the importance of a path-dependent distance for a time-dependent PDF. We then discuss the role of the information rate Γ=dLdt and relative entropy in non-equilibrium thermodynamic relations (entropy production rate, heat flux, dissipated work, non-equilibrium free energy, etc.), and various inequalities among them. Here, L is the information length representing the total number of statistically distinguishable states a PDF evolves through over time. We explore the implications of a geodesic solution in information geometry for self-organization and control.

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“…Often, these models follow two different approaches, one describing the collective behavior and properties by viewing the motors as catalytic agents of a chemical reaction 6,14 whereas the second one focuses on the individual description that analyzes the specific conformational changes occurring during motility [9][10][11][12] . From a more physical point of view, several models taking into account the stochastic and thermodynamic nature of the translational dynamics of a) Electronic mail: isholek@gmail.com molecular motors were proposed and used to describe some general features of molecular motor activity [15][16][17][18][19][20][21] . The essential ingredient to perform the description in these approaches is to provide a model for the energy landscape of the cyclic operation of motors [15][16][17]20,21 , however these models are barely related to the chemical reactions that drive the process.…”

Section: Introductionmentioning

confidence: 99%

Reconstructing the free-energy landscape associated to molecular motors processivity

López-Alamilla

Holek

2012

Biophysical Chemistry

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We propose a biochemical model providing the kinetic and energetic descriptions of the processivity dynamics of kinesin and dinein molecular motors. Our approach is a modified version of a well known model describing kinesin dynamics and considers the presence of a competitive inhibition reaction by ADP. We first first reconstruct a continuous free-energy landscape of the cycle catalyst process that allows us to calculate the number of steps given by a single molecular motor. Then, we calculate an analytical expression associated to the translational velocity and the stopping time of the molecular motor in terms of time and ATP concentration. An energetic interpretation of motor processivity is discussed in quantitative form by using experimental data. We also predict a time duration of collective processes that agrees with experimental reports.

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Thermodynamics of Isothermal Brownian Motors

Cited by 10 publications

References 8 publications

Optimal sequence for Parrondo games

Optimal sequence for Parrondo games

Information Geometry, Fluctuations, Non-Equilibrium Thermodynamics, and Geodesics in Complex Systems

Reconstructing the free-energy landscape associated to molecular motors processivity

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