Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12666/477
Title: Renormalization of stochastic differential equations with multiplicative noise using effective potential methods
Authors: Gagnon, Jean Sébastien
Hochberg, David
Pérez Mercader, Juan
Keywords: Polímeros dirigidos., Simulación;Directed Polymers., Simulation
Issue Date: 23-Dec-2020
Publisher: Physical Review E. covering statistical, nonlinear, biological, and soft matter physics
DOI: 10.1103/PhysRevE.102.062142
Published version: https://journals.aps.org/pre/abstract/10.1103/PhysRevE.102.062142
Citation: Physical Review E 102 (6)
Abstract: We present a method to renormalize stochastic differential equations subjected to multiplicative noise. The method is based on the widely used concept of effective potential in high-energy physics and has already been successfully applied to the renormalization of stochastic differential equations subjected to additive noise. We derive a general formula for the one-loop effective potential of a single ordinary stochastic differential equation (with arbitrary interaction terms) subjected to multiplicative Gaussian noise (provided the noise satisfies a certain normalization condition). To illustrate the usefulness (and limitations) of the method, we use the effective potential to renormalize a toy chemical model based on a simplified Gray-Scott reaction. In particular, we use it to compute the scale dependence of the toy model's parameters (in perturbation theory) when subjected to a Gaussian power-law noise with short time correlations.
URI: http://hdl.handle.net/20.500.12666/477
ISSN: 2470-0053
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