Gradient Einstein-type warped products: rigidity, existence and nonexistence results via a nonlinear PDE
Jos\'e Nazareno Vieira Gomes, Willian Isao Tokura

TL;DR
This paper characterizes the conditions for constructing gradient Einstein-type warped metrics, deriving a nonlinear PDE framework, and establishing nonexistence, rigidity, and construction results with explicit examples on Riemannian manifolds.
Contribution
It introduces necessary and sufficient conditions for gradient Einstein-type warped metrics, linking them to a nonlinear PDE and providing new nonexistence, rigidity, and construction results.
Findings
Derived a general Lichnerowicz equation for these metrics
Proved gradient estimates for solutions of a nonlinear elliptic PDE
Established nonexistence and rigidity results for certain warped metrics
Abstract
We establish the necessary and sufficient conditions for constructing gradient Einstein-type warped metrics. One of these conditions leads us to a general Lichnerowicz equation with analytic and geometric coefficients for this class of metrics on the space of warping functions. In this way, we prove gradient estimates for positive solutions of a nonlinear elliptic differential equation on a complete Riemannian manifold with associated Bakry-\'Emery Ricci tensor bounded from below. As an application, we provide nonexistence and rigidity results for a large class of gradient Einstein-type warped metrics. Furthermore, we show how to construct gradient Einstein-type warped metrics, and then we give explicit examples which are not only meaningful in their own right, but also help to justify our results.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum chaos and dynamical systems · Spectral Theory in Mathematical Physics · Matrix Theory and Algorithms
