This publication describes extremal particles in branching random walks with stretched exponential displacements via point process convergence and precise large deviations.
This publication sharpens asymptotic results for the largest fragment in self-similar fragmentation processes, proving almost sure convergence with explicit corrections.
This publication studies multivariate regular variation for Markov chains and random linear models, showing how innovations and chain structure determine tail behavior.
This publication studies extremes of branching random walks with heavy-tailed displacements, proving convergence to a clustered Cox process after nonlinear transformation.
This publication studies quenched behavior of random walks with sparse random drifts, showing the absence of strong quenched limit laws under heavy-tailed gaps.
This publication analyzes the rightmost particle in branching random walks with stretched exponential step-size tails, proving limit theorems across distinct tail regimes.
This publication studies kinetic-type differential equations via smoothing transforms, proving uniqueness and describing asymptotics through branching random walks
This publication derives precise upper large-deviation asymptotics for branching processes in random environments, including first-passage estimates in the subcritical case.
This publication studies asymptotics of k-regular self-similar fragmentations, including extremal fragment sizes and Gumbel limits for extinction times.
This publication establishes large deviation principles for the rightmost particle in branching random walks with stretched exponential step-size tails.
This publication studies fluctuations of limiting measures in critical Mandelbrot cascades, providing optimal estimates for their local behavior.
This publication establishes sharp large-deviation estimates for one-dimensional random walks in random environments, including precise slowdown probabilities in the sub-ballistic regime.
This publication studies Poissonian tails of canonical fixed points of the smoothing transform, with an application to the right tail of the Quicksort distribution.
This publication studies tail asymptotics for stationary distributions of Markov chains generated by random Lipschitz functions, with new results for random difference equations under subexponential assumptions.
