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Environmental contaminant dispersion models based on the Vladimirov-Taibleson p-adic pseudo-differential operator

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Abstract This research develops a new framework for modeling the dispersion of contaminants in non-Archimedean media using the Taibleson-Vladimirov $$D^{\alpha }$$ D α p-adic pseudo-differential operator. A p-adic differential equation is proposed and solved, modeling the dispersion of contaminants in a p-adic medium initially confined to a specific region. Additionally, it is analyzed how the p-adic heat kernel associated with the Taibleson-Vladimirov $$D^{\alpha }$$ D α operator serves as a powerful tool for understanding how contaminants disperse over time, making the heat kernel a cornerstone for mathematical models aimed at environmental applications in p-adic settings. Furthermore, through the heat equation associated with the Taibleson-Vladimirov $$D^{\alpha }$$ D α operator, the evolution of contaminant concentration over time is described. Finally, a stochastic fractional p-adic diffusion equation is formulated and solved, incorporating initial conditions, external sources, and random noise.
Title: Environmental contaminant dispersion models based on the Vladimirov-Taibleson p-adic pseudo-differential operator
Description:
Abstract This research develops a new framework for modeling the dispersion of contaminants in non-Archimedean media using the Taibleson-Vladimirov $$D^{\alpha }$$ D α p-adic pseudo-differential operator.
A p-adic differential equation is proposed and solved, modeling the dispersion of contaminants in a p-adic medium initially confined to a specific region.
Additionally, it is analyzed how the p-adic heat kernel associated with the Taibleson-Vladimirov $$D^{\alpha }$$ D α operator serves as a powerful tool for understanding how contaminants disperse over time, making the heat kernel a cornerstone for mathematical models aimed at environmental applications in p-adic settings.
Furthermore, through the heat equation associated with the Taibleson-Vladimirov $$D^{\alpha }$$ D α operator, the evolution of contaminant concentration over time is described.
Finally, a stochastic fractional p-adic diffusion equation is formulated and solved, incorporating initial conditions, external sources, and random noise.

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