Bochner formulas, functional inequalities and generalized Ricci flow
Eva Kopfer, Jeffrey Streets

TL;DR
This paper establishes sharp functional inequalities along generalized Ricci flow using Bochner formulas and introduces a twisted connection to analyze stochastic properties, providing new characterizations of the flow.
Contribution
It introduces a novel Bochner formula for the Bismut connection and defines a twisted connection to characterize generalized Ricci flow via functional inequalities.
Findings
Sharp Poincaré and log-Sobolev inequalities along Ricci flow
A new Bochner formula for the Bismut connection
Characterization of Ricci flow through Malliavin calculus
Abstract
As a consequence of the Bochner formula for the Bismut connection acting on gradients, we show sharp universal Poincar\'e and log-Sobolev inequalities along solutions to generalized Ricci flow. Using the two-form potential we define a twisted connection on spacetime which determines an adapted Brownian motion on the frame bundle, yielding an adapted Malliavin gradient on path space. We show a Bochner formula for this operator, leading to characterizations of generalized Ricci flow in terms of universal Poincar\'e and log-Sobolev type inequalities for the associated Malliavin gradient and Ornstein-Uhlenbeck operator.
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
TopicsGeometric Analysis and Curvature Flows · Geometry and complex manifolds · Advanced Neuroimaging Techniques and Applications
