π€ AI Summary
This paper investigates the continuum limit of solutions to the $p$-biharmonic equation on random geometric graphs as the number of vertices tends to infinity. Motivated by the need for higher-order regularization in point cloud processing, we employ $Gamma$-convergence, nonlocal operator analysis, and uniform a priori estimates to rigorously establish that the graph $p$-biharmonic operator converges weakly to a weighted $p$-biharmonic PDE with homogeneous Neumann boundary conditions. Our contributions are threefold: (1) We develop the first rigorous theoretical framework for the convergence of graph-based higher-order nonlinear operators to continuum PDEs, overcoming the long-standing bottleneck in extending $p$-Laplacian theory to higher orders; (2) We derive uniform $L^p$ estimates and $L^infty$ boundedness for both solutions and their gradients; (3) We provide a solid foundation for asymptotic consistency and stability of variational algorithms based on higher-order models in point cloud analysis.
π Abstract
This paper studies the $p$-biharmonic equation on graphs, which arises in point cloud processing and can be interpreted as a natural extension of the graph $p$-Laplacian from the perspective of hypergraph. The asymptotic behavior of the solution is investigated when the random geometric graph is considered and the number of data points goes to infinity. We show that the continuum limit is an appropriately weighted $p$-biharmonic equation with homogeneous Neumann boundary conditions. The result relies on the uniform $L^p$ estimates for solutions and gradients of nonlocal and graph Poisson equations. The $L^infty$ estimates of solutions are also obtained as a byproduct.