A matrix Li-Yau-Hamilton estimate for Kähler-Ricci flow

Lei Ni University of California at San Diego

Differential Geometry mathscidoc:1609.10008

Journal of Differential Geometry, 75, (2), 303-358, 2007
In this paper we prove a new matrix Li-Yau-Hamilton (LYH) estimate for K¨ahler-Ricci flow on manifolds with nonnegative bi- sectional curvature. The form of this new LYH estimate is obtained by the interpolation consideration originated in [Ch] by Chow. This new inequality is shown to be connected with Perelman’s entropy formula through a family of differential equalities. In the rest of the paper, we show several applications of this new estimate and its corresponding estimate for linear heat equation. These include a sharp heat kernel comparison theorem, generalizing the earlier result of Li and Tian [LT], a manifold version of Stoll’s theorem [St] on the characterization of ‘algebraic divisors’, and a localized monotonicity formula for analytic subvari- eties, which sharpens the Bishop volume comparison theorem. Motivated by the connection between the heat kernel estimate and the reduced volume monotonicity of Perelman [P], we prove a sharp lower bound of the fundamental solution to the forward conjugate heat equation, which in a certain sense dual to Perelman’s monotonicity of the reduced volume. As an application of this new monotonicity formula, we show that the blow-down limit of a certain type of long-time solution is a gradient expanding soliton, generalizing an earlier result of Cao. We also illustrate the connection between the new LYH estimate and the Hessian comparison theorem of [FIN] on the forward reduced distance. Localized monotonicity formulae on entropy and forward reduced volume are also derived.
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  title={A matrix Li-Yau-Hamilton estimate for Kähler-Ricci flow},
  author={Lei Ni},
  booktitle={Journal of Differential Geometry},
Lei Ni. A matrix Li-Yau-Hamilton estimate for Kähler-Ricci flow. 2007. Vol. 75. In Journal of Differential Geometry. pp.303-358. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20160908193140589857665.
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