Existence, Stability and Slow Dynamics of Spikes in a 1D Minimal Keller--Segel Model with Logistic Growth
Fanze Kong, Michael Ward, Juncheng Wei

TL;DR
This paper investigates the existence, stability, and slow dynamics of localized spike patterns in a 1D Keller--Segel chemotaxis model with logistic growth, using a novel singular limit approach based on small chemoattractant diffusivity.
Contribution
It introduces a new analytical framework for spike pattern analysis in Keller--Segel models with small chemoattractant diffusivity, including stability criteria and slow dynamics derivation.
Findings
N-spike equilibria can be destabilized by zero-eigenvalue crossing or Hopf bifurcation.
Explicit stability range for cellular diffusion rate d_1 is identified.
Derived a differential algebraic system governing slow spike dynamics.
Abstract
We analyze the existence, linear stability, and slow dynamics of localized 1D spike patterns for a Keller--Segel model of chemotaxis that includes the effect of logistic growth of the cellular population. Our analysis of localized patterns for this two-component reaction-diffusion (RD) model is based, not on the usual limit of a large chemotactic drift coefficient, but instead on the singular limit of an asymptotically small diffusivity of the chemoattractant concentration field. In the limit , steady-state and quasi-equilibrium 1D multi-spike patterns are constructed asymptotically. To determine the linear stability of steady-state -spike patterns we analyze the spectral properties associated with both the ''large'' and the ''small'' eigenvalues associated with the linearization of the Keller--Segel model. By analyzing a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMathematical Biology Tumor Growth · Gene Regulatory Network Analysis · Molecular Communication and Nanonetworks
