Recent works have derived and proven the large-population mean-field limit for several classes of particle-based stochastic reaction-diffusion (PBSRD) models. These limits correspond to systems of partial integral-differential equations (PIDEs) that generalize standard mass-action reaction-diffusion PDE models. In this work we derive and prove the next order fluctuation corrections to such limits, which we show satisfy systems of stochastic PIDEs with Gaussian noise. Numerical examples are presented to illustrate how including the fluctuation corrections can enable the accurate estimation of higher order statistics of the underlying PBSRD model
We develop numerical methods for stochastic reaction-diffusion systems based on approaches used for ...
Abstract. We study the asymptotic behaviour of some mesoscopic sto-chastic models for systems of rea...
Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, e...
Reaction-diffusion PDEs and particle-based stochastic reaction-diffusion (PBSRD) models are commonly...
We study the asymptotic behaviour of some mesoscopic stochastic models for systems of reacting and d...
AbstractWe consider a class of stochastic evolution models for particles diffusing on a lattice and ...
We consider a class of stochastic reaction-diffusion equations with additive noise. We show that in ...
We study the scaling properties of the non-equilibrium stationary states (NESS) of a reaction-diffus...
We consider a class of stochastic reaction-diffusion equations with additive noise. We show that in ...
This thesis aims at providing an understanding of certain scaling limits for kinetic models perturbe...
We introduce two different reaction diffusion models: evolution of one-cell popula- tions in the pre...
We develop numerical methods for stochastic reaction-diffusion systems based on approaches used for ...
AbstractA locally interacting particle system is studied which can be interpreted as a stochastic mo...
AbstractWe consider the continuous version of the Vicsek model with noise, proposed as a model for c...
Two algorithms that combine Brownian dynamics (BD) simulations with mean-field partial differential ...
We develop numerical methods for stochastic reaction-diffusion systems based on approaches used for ...
Abstract. We study the asymptotic behaviour of some mesoscopic sto-chastic models for systems of rea...
Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, e...
Reaction-diffusion PDEs and particle-based stochastic reaction-diffusion (PBSRD) models are commonly...
We study the asymptotic behaviour of some mesoscopic stochastic models for systems of reacting and d...
AbstractWe consider a class of stochastic evolution models for particles diffusing on a lattice and ...
We consider a class of stochastic reaction-diffusion equations with additive noise. We show that in ...
We study the scaling properties of the non-equilibrium stationary states (NESS) of a reaction-diffus...
We consider a class of stochastic reaction-diffusion equations with additive noise. We show that in ...
This thesis aims at providing an understanding of certain scaling limits for kinetic models perturbe...
We introduce two different reaction diffusion models: evolution of one-cell popula- tions in the pre...
We develop numerical methods for stochastic reaction-diffusion systems based on approaches used for ...
AbstractA locally interacting particle system is studied which can be interpreted as a stochastic mo...
AbstractWe consider the continuous version of the Vicsek model with noise, proposed as a model for c...
Two algorithms that combine Brownian dynamics (BD) simulations with mean-field partial differential ...
We develop numerical methods for stochastic reaction-diffusion systems based on approaches used for ...
Abstract. We study the asymptotic behaviour of some mesoscopic sto-chastic models for systems of rea...
Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, e...