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Ergodicity of reversible reaction diffusion processes
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  • Published: March 1990

Ergodicity of reversible reaction diffusion processes

  • Wan-Ding Ding1,
  • Richard Durrett2 &
  • Thomas M. Liggett3 

Probability Theory and Related Fields volume 85, pages 13–26 (1990)Cite this article

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  • 11 Citations

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Summary

Reaction-diffusion processes were introduced by Nicolis and Prigogine, and Haken. Existence theorems have been established for most models, but not much is known about ergodic properties. In this paper we study a class of models which have a reversible measure. We show that the stationary distribution is unique and is the limit starting from any initial distribution.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Anhui Normal University, Wuhu, People's Republic of China

    Wan-Ding Ding

  2. Department of Mathematics, Cornell University, 14853, Ithaca, NY, USA

    Richard Durrett

  3. Department of Mathematics, U.C.L.A., 90024, Los Angeles, CA, USA

    Thomas M. Liggett

Authors
  1. Wan-Ding Ding
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  2. Richard Durrett
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  3. Thomas M. Liggett
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Additional information

The work was begun while the first author was visiting Cornell and supported by the Chinese government. The initial results (for Schlögl's first model) was generalized while the three authors were visiting the Nankai Institute for Mathematics, Tianjin, People's Republic of China

Partially supported by the National Science Foundation and the Army Research Office through the Mathematical Sciences Institute at Cornell University

Partially supported by NSF grant DMS 86-01800

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Ding, WD., Durrett, R. & Liggett, T.M. Ergodicity of reversible reaction diffusion processes. Probab. Th. Rel. Fields 85, 13–26 (1990). https://doi.org/10.1007/BF01377624

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  • Received: 12 December 1988

  • Revised: 06 September 1989

  • Issue Date: March 1990

  • DOI: https://doi.org/10.1007/BF01377624

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Keywords

  • Stochastic Process
  • Probability Theory
  • Diffusion Process
  • Stationary Distribution
  • Mathematical Biology
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