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Entropy generation and the Fokker–Planck equation

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  • Lucia, Umberto

Abstract

Stochastic differential equations are important to model many complex systems. The Fokker–Planck equation is fundamental in statistical thermodynamic analysis and in the study of fluctuations in complex systems. Entropy generation is a fundamental quantity in the analysis of irreversibility. This paper develops a link between the Fokker–Planck equation and entropy generation. The result suggests linking the entropy generation approach also to statistical processes.

Suggested Citation

  • Lucia, Umberto, 2014. "Entropy generation and the Fokker–Planck equation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 256-260.
    • Handle: RePEc:eee:phsmap:v:393:y:2014:i:c:p:256-260
    DOI: 10.1016/j.physa.2013.09.028
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    References listed on IDEAS

    as
    1. Lucia, Umberto, 2013. "Stationary open systems: A brief review on contemporary theories on irreversibility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1051-1062.
    2. Wang, Qiuping A., 2005. "Non-quantum uncertainty relations of stochastic dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 26(4), pages 1045-1052.
    3. Lucia, Umberto, 2013. "Thermodynamic paths and stochastic order in open systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 3912-3919.
    4. Lucia, Umberto, 2010. "Maximum entropy generation and κ-exponential model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4558-4563.
    5. Lucia, Umberto, 2012. "Irreversibility in biophysical and biochemical engineering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 5997-6007.
    6. Lucia, Umberto, 2013. "Carnot efficiency: Why?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3513-3517.
    7. Sharma, Vivek & Kaila, Ville R.I. & Annila, Arto, 2009. "Protein folding as an evolutionary process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 851-862.
    8. Lucia, Umberto, 2007. "Irreversible entropy variation and the problem of the trend to equilibrium," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 289-292.
    9. Lucia, Umberto, 2009. "Irreversibility, entropy and incomplete information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4025-4033.
    10. Lucia, Umberto, 2008. "Statistical approach of the irreversible entropy variation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3454-3460.
    11. Lucia, U., 2012. "Maximum or minimum entropy generation for open systems?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(12), pages 3392-3398.
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    Citations

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    Cited by:

    1. Lucia, Umberto, 2014. "Entropy generation and cell growth with comments for a thermodynamic anticancer approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 107-118.
    2. Deng, Xinyang & Deng, Yong, 2014. "On the axiomatic requirement of range to measure uncertainty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 163-168.
    3. Lucia, Umberto, 2014. "Entropy generation approach to cell systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 1-11.
    4. Lucia, Umberto, 2015. "Quanta and entropy generation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 115-121.
    5. Lucia, Umberto, 2016. "Second law considerations on the third law: From Boltzmann and Loschmidt paradox to non equilibrium temperature," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 121-128.

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