Existence and uniqueness of global large-data solutions for the Chemotaxis-Navier-Stokes system in $\mathbb{R}^2$

Fuente: arXiv
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Main Authors: Xu, Fan, Liu, Bin
Format: Preprint
Published: 2025
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author Xu, Fan
Liu, Bin
author_facet Xu, Fan
Liu, Bin
contents This work investigates the Cauchy problem for the classical Chemotaxis-Navier-Stokes (CNS) system in $\mathbb{R}^2$. We establish the global existence and uniqueness of strong, classical, and arbitrarily smooth solutions under large initial data, which has not been addressed in the existing literature. The key idea is to first derive an entropy-energy estimate for initial data with low regularity, by leveraging the intrinsic entropy structure of the system. Building on this foundation, we then obtain higher-order energy estimates for smoother initial data via a bootstrap argument, in which the parabolic nature of the CNS system plays a crucial role in the iterative control of regularity.
format Preprint
id arxiv_https___arxiv_org_abs_2506_15434
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Existence and uniqueness of global large-data solutions for the Chemotaxis-Navier-Stokes system in $\mathbb{R}^2$
Xu, Fan
Liu, Bin
Analysis of PDEs
This work investigates the Cauchy problem for the classical Chemotaxis-Navier-Stokes (CNS) system in $\mathbb{R}^2$. We establish the global existence and uniqueness of strong, classical, and arbitrarily smooth solutions under large initial data, which has not been addressed in the existing literature. The key idea is to first derive an entropy-energy estimate for initial data with low regularity, by leveraging the intrinsic entropy structure of the system. Building on this foundation, we then obtain higher-order energy estimates for smoother initial data via a bootstrap argument, in which the parabolic nature of the CNS system plays a crucial role in the iterative control of regularity.
title Existence and uniqueness of global large-data solutions for the Chemotaxis-Navier-Stokes system in $\mathbb{R}^2$
topic Analysis of PDEs
url https://arxiv.org/abs/2506.15434