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Nonlocal Fisher--KPP propagation with heavy tails

Abstract

We study a nonlocal Fisher--KPP equation on the real line with compactly supported initial data. The reaction satisfies f(s)≤ f′(0)s for 0≤ s≤1, with a power bound on f′(0)s−f(s) near zero. For continuous even probability kernels J comparable to |x|−γ, γ>1, we prove a global two-sided estimate and locate every fixed level set with a bounded error in log|x|. The propagation scale is exp(f'(0)t/γ) for every γ>1. This differs sharply from the free-boundary propagation studied by Du and Ni \cite{DuNiJEMS}. For polynomial kernel tails, spreading in their model has linear, algebraic or tlog t growth. We also obtain arrival-time and weighted-integral estimates and identify a spatial tail coefficient when |x|γJ(x) has a positive limit.

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BibTeX
@misc{hu2026nonlocal,
  title = {{Nonlocal Fisher--KPP propagation with heavy tails}},
  author = {Yuanyang Hu},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.30986},
  eprint = {2610.30986},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.30986},
}
RIS
TY  - UNPB
TI  - Nonlocal Fisher--KPP propagation with heavy tails
AU  - Yuanyang Hu
PY  - 2026
DA  - 2026/10/22
PB  - arXiv
DO  - 10.48550/arxiv.2610.30986
UR  - https://arxiv.org/abs/2610.30986
AB  - We study a nonlocal Fisher--KPP equation on the real line with compactly supported initial data. The reaction satisfies f(s)≤ f^′(0)s for 0≤ s≤1, with a power bound on f^′(0)s−f(s) near zero. For continuous even probability kernels J comparable to |x|^−γ, γ>1, we prove a global two-sided estimate and locate every fixed level set with a bounded error in log|x|. The propagation scale is exp(f'(0)t/γ) for every γ>1. This differs sharply from the free-boundary propagation studied by Du and Ni \cite{DuNiJEMS}. For polynomial kernel tails, spreading in their model has linear, algebraic or tlog t growth. We also obtain arrival-time and weighted-integral estimates and identify a spatial tail coefficient when |x|^γJ(x) has a positive limit.
ER  -