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Cycle symmetry, limit theorems, and fluctuation theorems for diffusion processes on the circle

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  • Ge, Hao
  • Jia, Chen
  • Jiang, Da-Quan

Abstract

Cyclic structure and dynamics are of great interest in both the fields of stochastic processes and nonequilibrium statistical physics. In this paper, we find a new symmetry of the Brownian motion named as the quasi-time-reversal invariance. It turns out that such an invariance of the Brownian motion is the key to prove the cycle symmetry for diffusion processes on the circle, which says that the distributions of the forming times of the forward and backward cycles, given that the corresponding cycle is formed earlier than the other, are exactly the same. With the aid of the cycle symmetry, we prove the strong law of large numbers, functional central limit theorem, and large deviation principle for the sample circulations and net circulations of diffusion processes on the circle. The cycle symmetry is further applied to obtain various types of fluctuation theorems for the sample circulations, net circulation, and entropy production rate.

Suggested Citation

  • Ge, Hao & Jia, Chen & Jiang, Da-Quan, 2017. "Cycle symmetry, limit theorems, and fluctuation theorems for diffusion processes on the circle," Stochastic Processes and their Applications, Elsevier, vol. 127(6), pages 1897-1925.
    • Handle: RePEc:eee:spapps:v:127:y:2017:i:6:p:1897-1925
    DOI: 10.1016/j.spa.2016.09.011
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    References listed on IDEAS

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    1. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037, Decembrie.
    2. U. Seifert, 2008. "Stochastic thermodynamics: principles and perspectives," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 64(3), pages 423-431, August.
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    Cited by:

    1. Chen, Xian & Jia, Chen, 2020. "Mathematical foundation of nonequilibrium fluctuation–dissipation theorems for inhomogeneous diffusion processes with unbounded coefficients," Stochastic Processes and their Applications, Elsevier, vol. 130(1), pages 171-202.

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