Efficient stochastic asymptotic-preserving scheme for tumor growth models with uncertain parameters

Fuente: arXiv
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Autores principales: Jiang, Ning, Liu, Liu, Yu, Huimin
Formato: Preprint
Publicado: 2025
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author Jiang, Ning
Liu, Liu
Yu, Huimin
author_facet Jiang, Ning
Liu, Liu
Yu, Huimin
contents In this paper, we investigate a class of tumor growth models governed by porous medium-type equations with uncertainties arisen from the growth function, initial condition, tumor support radius or other parameters in the model. We develop a stochastic asymptotic preservation (s-AP) scheme in the generalized polynomial chaos-stochastic Galerkin (gPC-SG) framework, which remains robust for all index parameters $m\geq 2$. The regularity of the solution to porous medium equations in the random space is studied, and we show the s-AP property, ensuring the convergence of SG system on the continuous level to that of Hele-Shaw dynamics as $m \to \infty$. Our numerical experiments, including capturing the behaviors such as finger-like projection, proliferating, quiescent and dead cell's evolution, validate the accuracy and efficiency of our designed scheme. The numerical results can describe the impact of stochastic parameters on tumor interface evolutions and pattern formations.
format Preprint
id arxiv_https___arxiv_org_abs_2503_11468
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Efficient stochastic asymptotic-preserving scheme for tumor growth models with uncertain parameters
Jiang, Ning
Liu, Liu
Yu, Huimin
Numerical Analysis
35K55, 35Q92, 35R60, 65C20
In this paper, we investigate a class of tumor growth models governed by porous medium-type equations with uncertainties arisen from the growth function, initial condition, tumor support radius or other parameters in the model. We develop a stochastic asymptotic preservation (s-AP) scheme in the generalized polynomial chaos-stochastic Galerkin (gPC-SG) framework, which remains robust for all index parameters $m\geq 2$. The regularity of the solution to porous medium equations in the random space is studied, and we show the s-AP property, ensuring the convergence of SG system on the continuous level to that of Hele-Shaw dynamics as $m \to \infty$. Our numerical experiments, including capturing the behaviors such as finger-like projection, proliferating, quiescent and dead cell's evolution, validate the accuracy and efficiency of our designed scheme. The numerical results can describe the impact of stochastic parameters on tumor interface evolutions and pattern formations.
title Efficient stochastic asymptotic-preserving scheme for tumor growth models with uncertain parameters
topic Numerical Analysis
35K55, 35Q92, 35R60, 65C20
url https://arxiv.org/abs/2503.11468