scholarly journals Traveling fronts in self-replicating persistent random walks with multiple internal states

2020 ◽  
Vol 22 (8) ◽  
pp. 083034
Author(s):  
Keisuke Ishihara ◽  
Ashish B George ◽  
Ryan Cornelius ◽  
Kirill S Korolev
2020 ◽  
Author(s):  
Keisuke Ishihara ◽  
Ashish B. George ◽  
Ryan Cornelius ◽  
Kirill S. Korolev

Self-activation coupled to a transport mechanism results in traveling waves that describe polymerization reactions, forest fires, tumor growth, and even the spread of epidemics. Diffusion is a simple and commonly used model of particle transport. Many physical and biological systems are, however, better described by persistent random walks that switch between multiple states of ballistic motion. So far, traveling fronts in persistent random walk models have only been analyzed in special, simplified cases. Here, we formulate the general model of reaction-transport processes in such systems and show how to compute the expansion velocity for arbitrary number of states. For the two-state model, we obtain a closed-form expression for the velocity and report how it is affected by different transport and replication parameters. We also show that nonzero death rates result in a discontinuous transition from quiescence to propagation. We compare our results to a recent observation of a discontinuous onset of propagation in microtubule asters and comment on the universal nature of the underlying mechanism.


2018 ◽  
Vol 2018 (8) ◽  
pp. 083209 ◽  
Author(s):  
Roberto Artuso ◽  
Giampaolo Cristadoro ◽  
Manuele Onofri ◽  
Mattia Radice

2010 ◽  
Vol 10 (02) ◽  
pp. 161-196 ◽  
Author(s):  
S. HERRMANN ◽  
P. VALLOIS

We study a family of memory-based persistent random walks and we prove weak convergences after space-time rescaling. The limit processes are not only Brownian motions with drift. We have obtained a continuous but non-Markov process (Zt) which can be easily expressed in terms of a counting process (Nt). In a particular case the counting process is a Poisson process, and (Zt) permits to represent the solution of the telegraph equation. We study in detail the Markov process ((Zt, Nt); t ≥ 0).


2019 ◽  
Vol 99 (1) ◽  
Author(s):  
Davide Vergni ◽  
Stefano Berti ◽  
Angelo Vulpiani ◽  
Massimo Cencini

Bernoulli ◽  
2020 ◽  
Vol 26 (2) ◽  
pp. 858-892
Author(s):  
Peggy Cénac ◽  
Basile de Loynes ◽  
Yoann Offret ◽  
Arnaud Rousselle

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