Well-Posedness of Pseudo-Parabolic Gradient Systems with State-Dependent Dynamics
Harbir Antil, Daiki Mizuno, Ken Shirakawa, Naotaka Ukai
TL;DR
This work develops a general well-posedness theory for pseudo-parabolic gradient systems with state-dependent dynamics, proving existence of energy-dissipating solutions and uniqueness with continuous dependence on initial data. The analysis combines time-discretization, convex analysis, and Mosco/Γ-convergence to handle nonlinear, variable-coefficient operators. The framework is demonstrated through two applications: an anisotropic image-denoising model and a pseudo-parabolic anisotropic KWC-type grain-boundary model, both fitting into the abstract $( ext{S})_ u$ structure. The results advance nonlinear evolution theory with state-dependent dynamics and have implications for materials science and image processing.
Abstract
This paper develops a general mathematical framework for pseudo-parabolic gradient systems with state-dependent dynamics. The state dependence is induced by variable coefficient fields in the governing energy functional. Such coefficients arise naturally in scientific and technological models, including state-dependent mobilities in KWC-type grain boundary motion and variable orientation-adaptation operators in anisotropic image denoising. We establish two main results: the existence of energy-dissipating solutions, and the uniqueness and continuous dependence on initial data. The proposed framework yields a general well-posedness theory for a broad class of nonlinear evolutionary systems driven by state-dependent operators. As illustrative applications, we present an anisotropic image-denoising model and a new pseudo-parabolic KWC-type model for anisotropic grain boundary motion, and prove that both fit naturally within the abstract structure of $(\mathrm{S})_ν$.
