A Version of the Random Directed Forest and its Convergence to the Brownian Web

Glauco Valle () and Leonel Zuaznábar ()
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Glauco Valle: Universidade Federal do Rio de Janeiro
Leonel Zuaznábar: Universidade de São Paulo

Journal of Theoretical Probability, 2023, vol. 36, issue 2, 948-1002

Abstract: Abstract Several authors have studied convergence in distribution to the Brownian web under diffusive scaling of systems of Markovian random walks. In a paper by R. Roy, K. Saha and A. Sarkar, convergence to the Brownian web is proved for a system of coalescing random paths—the random directed forest—which are not Markovian. Paths in the random directed forest do not cross each other before coalescence. Here, we study a variation of the random directed forest where paths can cross each other and prove convergence to the Brownian web. This provides an example of how the techniques to prove convergence to the Brownian web for systems allowing crossings can be applied to non-Markovian systems.

Keywords: Coalescing random walks; Brownian web; Invariance principle; Diffusive scaling limit; Random directed forest; Primary; 60K35 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10959-022-01202-z

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