Non-local tug-of-war with noise for the geometric fractional $p$-Laplacian
Marta Lewicka

TL;DR
This paper introduces a non-local, non-linear averaging framework for the fractional p-Laplacian, proving convergence of associated dynamic programming solutions and interpreting them through a noisy tug-of-war game model.
Contribution
It defines new averaging operators for the fractional p-Laplacian, establishes their connection to viscosity solutions, and interprets these solutions via a novel non-local tug-of-war game with noise.
Findings
A family of non-local averaging operators approximates the fractional p-Laplacian.
Solutions to the dynamic programming principle converge uniformly to viscosity solutions.
The solutions can be interpreted as values of a noisy tug-of-war game.
Abstract
This paper concerns the fractional -Laplace operator in non-divergence form, which has been introduced in [Bjorland, Caffarelli, Figalli (2012)]. For any and we first define two families of non-local, non-linear averaging operators, parametrised by and defined for all bounded, Borel functions . We prove that emerges as the -order coefficient in the expansion of the deviation of each -average from the value , in the limit of the domain of averaging exhausting an appropriate cone in at the rate . Second, we consider the -dynamic programming principles modeled on the first average, and show that their solutions converge uniformly as , to viscosity solutions of the homogeneous non-local…
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Taxonomy
TopicsNonlinear Partial Differential Equations · Geometric Analysis and Curvature Flows · Numerical methods in inverse problems
