English

Principal eigenvalues for k-Hessian operators by maximum principle methods

Analysis of PDEs 2020-01-01 v1

Abstract

For fully nonlinear kk-Hessian operators on bounded strictly (k1)(k-1)-convex domains Ω\Omega in RN{\mathbb R}^N, a characterization of the principal eigenvalue associated to a kk-convex and negative principal eigenfunction will be given as the supremum over values of a spectral parameter for which admissible viscosity supersolutions obey a minimum principle. The admissibility condition is phrased in terms of the natural closed convex cone Σk\Sigma_k in the space of symmetric N by N matrices, which is an elliptic set in the sense of Krylov [Trans. AMS, 1995] and which corresponds to using kk-convex functions as admissibility constraints in the formulation of viscosity subsolutions and supersolutions. Moreover, the associated principal eigenfunction is constructed by an iterative viscosity solution technique, which exploits a compactness property which results from the establishment of a global H\"{o}lder estimate for the unique kk-convex solutions of the approximating equations.

Keywords

Cite

@article{arxiv.1912.09226,
  title  = {Principal eigenvalues for k-Hessian operators by maximum principle methods},
  author = {Isabeau Birindelli and Kevin R. Payne},
  journal= {arXiv preprint arXiv:1912.09226},
  year   = {2020}
}

Comments

41 pages, submitted for publication

R2 v1 2026-06-23T12:51:04.373Z