Quantitative homogenization of forced geometric motions through random fields of obstacles
Julian Fischer, Jonas Ingmanns

TL;DR
This paper proves a quantitative homogenization result for interfaces moving through sparse random obstacles, showing large-scale effective motion with error estimates, even allowing for local pinning effects, advancing understanding of interface dynamics in disordered media.
Contribution
It introduces a homogenization framework for forced mean curvature flow with obstacles, accommodating local pinning and negative forcing, unlike previous models requiring positive forcing everywhere.
Findings
Effective large-scale interface motion governed by constant speed.
Error estimate for front arrival times of order ε^{1/9-}.
Applicable to models with local pinning and obstacles.
Abstract
We establish a quantitative homogenization result for an interface moving through a field of sufficiently sparse but possibly impenetrable random obstacles. From a physical viewpoint, such problems arise e.g. in the context of the motion of dislocations or magnetic domain walls in a material with impurities. More precisely, given an interface moving by forced mean curvature flow -- with a positive global driving force plus a spatially fluctuating (negative) driving force modeling the obstacles -- , we prove that the effective large-scale behavior of the forward front is governed by a constant-speed effective motion. For typical values of the global forcing, on large scales of the order we obtain a (relative) error estimate for arrival times of the front of the order . Previous stochastic homogenization results for forced mean curvature motion…
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Taxonomy
TopicsAdvanced Mathematical Modeling in Engineering · Quantum chaos and dynamical systems · Diffusion and Search Dynamics
