Mathematical analysis and numerical simulation of free boundary problem modeling tumor evolution

In this paper, we consider a free boundary problem that arises in the mathematical modeling of cancer. In this model, a parameter η is introduced to represent the killing rate of cancer cells by the T cells. We study the existence of steady state solution to the free boundary problem and its linear stability when the parameter η satisfies certain conditions. The uniqueness and existence of the global solution to the model are then discussed and properties of the solution are also obtained. We derive a finite difference algorithm for the problem and analyze the stability of the algorithm. Finally we perform numerical simulations to validate the theoretical results.

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Publication Details

Journal
Applicable Analysis
Published
2026-09-25
DOI
https://doi.org/10.1080/00036811.2026.2736067
Primary Topic
Mathematical Biology Tumor Growth
Type
article
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article

Mathematical analysis and numerical simulation of free boundary problem modeling tumor evolution

Xuming Xie, Amal Aldakhil
Applicable Analysis
Mathematical Biology Tumor Growth
article

Mathematical analysis and numerical simulation of free boundary problem modeling tumor evolution

Xuming Xie, Amal Aldakhil
article en

Abstract

In this paper, we consider a free boundary problem that arises in the mathematical modeling of cancer. In this model, a parameter η is introduced to represent the killing rate of cancer cells by the T cells. We study the existence of steady state solution to the free boundary problem and its linear stability when the parameter η satisfies certain conditions. The uniqueness and existence of the global solution to the model are then discussed and properties of the solution are also obtained. We derive a finite difference algorithm for the problem and analyze the stability of the algorithm. Finally we perform numerical simulations to validate the theoretical results.

Applicable Analysis
Morgan State University (US)
Openalex Percentile: Top 13%
Mathematical Biology Tumor Growth
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