We consider second-order divergence form uniformly parabolic and elliptic PDEs with bounded and $VMO_{x}$ leading coefficients and possibly linearly growing lower-order coefficients. We look for solutions which are summable to the $p$th power with respect to the usual Lebesgue measure along with their first derivatives with respect to the spatial variables.
We show that two classically known properties of positive supersolutions of uniformly elliptic PDEs, the boundary point principle (Hopf lemma) and global integrability, can be quantified with respect to each other. We obtain an extension to the boundary of the de Giorgi-Moser weak Harnack inequality, optimal with respect to the norms involved, for equations in divergence form.
We consider a family of holomorphic PDEs whose singular locus is given by the zero set of an analytic map $P$ with $P(0)=0$. Our goal is to establish conditions for the existence and uniqueness of formal power series solutions and to determine their divergence rate. In fact, we prove that the solution is Gevrey in $P$, giving new information on divergency while compared to the classical Gevrey classes. If $P$ is not singular at $0$, we also provide Poincaré conditions to recover convergent solutions. Our strategy is to extend the dimension and lift the given PDE to a problem where results of s…
Differential Harnack inequalities and maximum principles of Morel-Oswald type for elliptic PDE in divergence form
PUC-Rio, Departamento de Matematica（天主教里约热内卢大学数学系）；Université Sorbonne Paris Nord, CNRS UMR 7539, Laboratoire Analyse, Géométrie et Applications（索邦巴黎北大学，法国国家科学研究中心UMR 7539，分析与几何应用实验室）
Characterisation of homogenisation for nonlocal diffusion by local topologies
TU Hamburg（汉堡工业大学）；School of Applied Mathematics and Informatics, University of Osijek（奥西耶克大学应用数学与信息学院）；Department of Mathematics, Faculty of Science, University of Zagreb（萨格勒布大学理学院数学系）；TU Bergakademie Freiberg（弗莱贝格矿业技术大学）
Since its introduction in 2017, physics-informed deep learning (PIDL) has garnered growing popularity in understanding the evolution of systems governed by physical laws in terms of partial differential equations (PDEs). However, empirical evidence points to the limitations of PIDL for learning certain types of PDEs. In this paper, we (a) present the challenges in training PIDL architecture, (b) contrast the performance of PIDL architecture in learning a first order scalar hyperbolic conservation law and its parabolic counterpart, (c) investigate the effect of training data sampling, which cor…
