Constructing abundant exact stochastic solutions to the Newell-Whitehead-Segel equation with multiplicative advection noise

Abeer H. Alblowy , Wael W. Mohammed , Hessa W. Alshammari , Elsayed M. Elsayed

Electronic Research Archive ›› 2026, Vol. 34 ›› Issue (2) : 922 -937.

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Electronic Research Archive ›› 2026, Vol. 34 ›› Issue (2) :922 -937. DOI: 10.3934/era.2026043
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Constructing abundant exact stochastic solutions to the Newell-Whitehead-Segel equation with multiplicative advection noise
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Abstract

In this work, we consider the stochastic Newell-Whitehead-Segel (SNWS) equation, which is forced in the Itô sense by multiplicative advection noise. We demonstrate that the solution of the SNWS equation can be discovered by solving certain deterministic counterparts of the Newell- Whitehead-Segel equation with an extra diffusion term (DNWS), and then the results are combined with a solution for stochastic ordinary differential equations. We use two techniques to solve the DNWS equation: the (G′/G) -expansion method and the exp(−ψ(η))-expansion method. The purpose of studying the Newell-Whitehead-Segel equation with multiplicative noise is to explore how stochastic fluctuations influence the stability and evolution of patterns near a bifurcation. Incorporating noise provides a more realistic description of physical systems and reveals impacts that are omitted from the deterministic model, such as changing thresholds, different pattern structures, and increased variability. Therefore, we use a MATLAB tool to exhibit numerous 3D and 2D graphs that show how multiplicative advection noise impacts the solutions of the SNWS equation.

Keywords

noise strength / simulation / stochastic solutions / analytical methods / mathematical model / exact solutions

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Abeer H. Alblowy, Wael W. Mohammed, Hessa W. Alshammari, Elsayed M. Elsayed. Constructing abundant exact stochastic solutions to the Newell-Whitehead-Segel equation with multiplicative advection noise. Electronic Research Archive, 2026, 34 (2) : 922-937 DOI:10.3934/era.2026043

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