English

Reflecting random walks in curvilinear wedges

Probability 2022-02-15 v2

Abstract

We study a random walk (Markov chain) in an unbounded planar domain whose boundary is described by two curves of the form x2=a+x1β+x_2 = a^+ x_1^{\beta^+} and x2=ax1βx_2 = -a^- x_1^{\beta^-}, with x10x_1 \geq 0. In the interior of the domain, the random walk has zero drift and a given increment covariance matrix. From the vicinity of the upper and lower sections of the boundary, the walk drifts back into the interior at a given angle α+\alpha^+ or α\alpha^- to the relevant inwards-pointing normal vector. Here we focus on the case where α+\alpha^+ and α\alpha^- are equal but opposite, which includes the case of normal reflection. For 0β+,β<10 \leq \beta^+, \beta^- < 1, we identify the phase transition between recurrence and transience, depending on the model parameters, and quantify recurrence via moments of passage times.

Keywords

Cite

@article{arxiv.2001.06685,
  title  = {Reflecting random walks in curvilinear wedges},
  author = {Mikhail V. Menshikov and Aleksandar Mijatović and Andrew R. Wade},
  journal= {arXiv preprint arXiv:2001.06685},
  year   = {2022}
}

Comments

32 pages, 4 figures; v2: minor revisions

R2 v1 2026-06-23T13:14:43.661Z