Local survival of spread of infection among biased random walks

Rangel Baldasso, Alexandre Stauffer

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

We study infection spread among biased random walks on Zd . The random walks move independently and an infected particle is placed at the origin at time zero. Infection spreads instantaneously when particles share the same site and there is no recovery. If the initial density of particles is small enough, the infected cloud travels in the direction of the bias of the random walks, implying that the infection does not survive locally. When the density is large, the infection spreads to the whole Zd . The proofs rely on two different techniques. For the small density case, we use a description of the infected cloud through genealogical paths, while the large density case relies on a renormalization scheme.

Original languageEnglish
Article number135
JournalElectronic Journal of Probability
Volume27
DOIs
StatePublished - 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022, Institute of Mathematical Statistics. All rights reserved.

Funding

*Supported by EPSRC Fellowship EP/N004566/1. †Mathematical Institute, Leiden University, P.O. Box 9512, 2300 RA Leiden, The Netherlands. E-mail: [email protected] ‡Università Roma Tre, Dip. di Matematica e Fisica, Largo S. Murialdo 1, 00146, Rome, Italy; University of Bath, Dept of Mathematical Sciences, BA2 7AY Bath, UK. E-mail: [email protected]

FundersFunder number
Engineering and Physical Sciences Research CouncilEP/N004566/1

    Keywords

    • biased random walks
    • infection processes
    • interacting particle systems

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