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March 16, 2026Communications in Nonlinear Science and Numerical Simulation2 citationsOpen Access

A time-fractional Fisher–KPP equation for tumor growth: Analysis and numerical simulation

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MFMarvin FritzAustrian Academy of SciencesNKNikos I. KavallarisKarlstad University

Key Points

  • The aim is to analyze and simulate a time-fractional Fisher-KPP equation for tumor growth, incorporating memory effects in population dynamics.
  • Analyzed the time-fractional Fisher-KPP equation using Galerkin compactness methods.
  • Proved local weak well-posedness of solutions.
  • Developed a convolution-quadrature finite element method for numerical simulations.
  • Validated simulations to compare dynamics with conventional models.
  • Established global well-posedness for sufficiently small initial data.
  • Simulations highlighted distinct behaviors compared to Caputo-in-time formulation.
  • Demonstrated physical consistency of the model in capturing tumor growth dynamics.

Abstract

• Physically consistent time-fractional Fisher-KPP equation is analyzed. • Local weak well-posedness is proved by Galerkin compactness methods. • Global existence is obtained for sufficiently small initial data. • A graded convolution-quadrature FEM is developed for the model. • Simulations distinguish the model from the Caputo-in-time formulation. We study a time-fractional Fisher–KPP equation involving a Riemann–Liouville fractional derivative acting on the diffusion term, as derived by Angstmann and Henry (Entropy, 22:1035, 2020). The model captures memory effects in diffusive population dynamics and serves as a framework for tumor growth modeling. We first establish local well-posedness of weak solutions. The analysis combines a Galerkin approximation with a refined a priori estimate based on a Bihari–Henry–Gronwall inequality, addressing the nonlinear coupling between the fractional diffusion and the reaction term. For small initial data, we further prove global well-posedness and asymptotic stability. A numerical method based on a nonuniform convolution quadrature scheme is then proposed and validated. Simulations demonstrate distinct dynamical behaviors compared to conventional formulations, emphasizing the physical consistency of the present model in describing tumor progression.

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Cite This Study

Fritz et al. (2026) studied this question.

synapsesocial.com/papers/69b79df38166e15b153ab254https://doi.org/10.1016/j.cnsns.2026.109911
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