On well-posedness for non-autonomous parabolic Cauchy problems with rough initial data
Hedong Hou
TL;DR
This paper develops a comprehensive well-posedness theory for non-autonomous parabolic Cauchy problems in divergence form with rough, complex-valued coefficients $A(t,x)$. By leveraging weighted tent spaces and homogeneous Hardy–Sobolev Besov-type spaces, it ties initial data regularity to time-weighted gradient control of weak solutions, and constructs robust propagator and Duhamel frameworks with off-diagonal decay estimates. The main contributions include existence, uniqueness, and explicit representation formulas for homogeneous and inhomogeneous problems, Lions-type equations, and a precise trace/continuity theory in tents spaces, extended to homogeneous Besov spaces via interpolation. The results significantly advance the understanding of parabolic systems with rough coefficients and rough initial data, offering sharp, scalable tools for analysis and potential stochastic applications. Collectively, the work provides a complete, modular picture of well-posedness across a broad spectrum of initial data spaces and time-dependent coefficient matrices.
Abstract
We establish a complete picture for existence, uniqueness, and representation of weak solutions to non-autonomous parabolic Cauchy problems of divergence type. The coefficients are only assumed to be uniformly elliptic, bounded, measurable, and complex-valued, without any additional regularity or symmetry conditions. The initial data are tempered distributions taken in homogeneous Hardy--Sobolev spaces $\dot{H}^{s,p}$, and source terms belong to certain scales of weighted tent spaces. Weak solutions are constructed with their gradients in weighted tent spaces $T^{p}_{s/2}$. Analogous results are also exhibited for initial data in homogeneous Besov spaces $\dot{B}^{s}_{p,p}$.
