Active particle in one dimension subjected to resetting with memory
The study of diffusion with preferential returns to places visited in the past has attracted
increased attention in recent years. In these highly non-Markov processes, a standard …
increased attention in recent years. In these highly non-Markov processes, a standard …
Diffusion with preferential relocation in a confining potential
We study the relaxation of a diffusive particle confined in an arbitrary external potential and
subject to a non-Markovian resetting protocol. With a constant rate r, a previous time τ …
subject to a non-Markovian resetting protocol. With a constant rate r, a previous time τ …
Central limit theorems for the monkey walk with steep memory kernel
ES Boci, C Mailler - arxiv preprint arxiv:2409.02861, 2024 - arxiv.org
The monkey walk is a stochastic process defined as the trajectory of a walker that moves on
$\mathbb R^ d $ according to a Markovian generator, except at some random" relocation" …
$\mathbb R^ d $ according to a Markovian generator, except at some random" relocation" …
Random walks with long-range memory on networks
AG Guerrero-Estrada, AP Riascos… - Chaos: An Interdisciplinary …, 2025 - pubs.aip.org
We study an exactly solvable random walk model with long-range memory on arbitrary
networks. The walker performs unbiased random steps to nearest-neighbor nodes and …
networks. The walker performs unbiased random steps to nearest-neighbor nodes and …
Power-law relaxation of a confined diffusing particle subject to resetting with memory
We study the relaxation of a Brownian particle with long range memory under confinement in
one dimension. The particle diffuses in an arbitrary confining potential and resets at random …
one dimension. The particle diffuses in an arbitrary confining potential and resets at random …
Height of weighted recursive trees with sub-polynomially growing total weight
M Pain, D Sénizergues - Annales de l'Institut Henri Poincare (B) …, 2024 - projecteuclid.org
Weighted recursive trees are built by adding successively vertices with predetermined
weights to a tree: each new vertex is attached to a parent chosen at random with probability …
weights to a tree: each new vertex is attached to a parent chosen at random with probability …