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In this paper, we solve the longstanding Gaussian curvature conjecture of a minimal graph $S$ over the unit disk. The conjecture asserts that for any minimal graph above the unit disk, the Gaussian curvature at the point directly above the…

Differential Geometry · Mathematics 2025-06-10 David Kalaj , Petar Melentijevic

We obtain a gradient estimate for the Gauss maps from complete spacelike constant mean curvature hypersurfaces in Minkowski space into the hyperbolic space. As applications, we prove a Bernstein theorem which says that if the image of the…

dg-ga · Mathematics 2008-02-03 Huai-Dong Cao , Ying Shen , Shunhui Zhu

We describe how to approximate the Riemann curvature tensor as well as sectional curvatures on possibly infinite-dimensional shape spaces that can be thought of as Riemannian manifolds. To this end, we extend the variational time…

Numerical Analysis · Mathematics 2019-12-17 Alexander Effland , Behrend Heeren , Martin Rumpf , Benedikt Wirth

Recently, the author and Melentijevi\'c resolved the longstanding Gaussian curvature problem by proving the sharp inequality \[ |\mathcal{K}| < c_0 = \frac{\pi^2}{2} \] for minimal graphs over the unit disk, evaluated at the point of the…

Differential Geometry · Mathematics 2025-08-26 David Kalaj

We show that a differentiable function on the 2-Wasserstein space is geodesically convex if and only if it is also convex along a larger class of curves which we call `acceleration-free'. In particular, the set of acceleration-free curves…

Functional Analysis · Mathematics 2023-06-21 Guy Parker

We introduce new results about the shape derivatives of scalar- and vector-valued functions, extending the results from (Dogan-Nochetto 2012) to more general surface energies. They consider surface energies defined as integrals over…

Optimization and Control · Mathematics 2017-08-25 Aníbal Chicco-Ruiz , Pedro Morin , M. Sebastian Pauletti

If $u : \Omega\subset \mathbb{R}^d \to {\rm X}$ is a harmonic map valued in a metric space ${\rm X}$ and ${\sf E} : {\rm X} \to \mathbb{R}$ is a convex function, in the sense that it generates an ${\rm EVI}_0$-gradient flow, we prove that…

Metric Geometry · Mathematics 2021-07-21 Hugo Lavenant , Léonard Monsaingeon , Luca Tamanini , Dmitry Vorotnikov

A common method for estimating the Hessian operator from random samples on a low-dimensional manifold involves locally fitting a quadratic polynomial. Although widely used, it is unclear if this estimator introduces bias, especially in…

Statistics Theory · Mathematics 2025-09-10 Chih-Wei Chen , Hau-Tieng Wu

In this paper we construct smooth Riemannian metrics on the sphere which admit smooth Zoll families of minimal hypersurfaces. This generalizes a theorem of Guillemin for the case of geodesics. The proof uses the Nash-Moser Inverse Function…

Differential Geometry · Mathematics 2021-12-03 Lucas Ambrozio , Fernando C. Marques , André Neves

We further research on the accelerated optimization phenomenon on Riemannian manifolds by introducing accelerated global first-order methods for the optimization of $L$-smooth and geodesically convex (g-convex) or $\mu$-strongly g-convex…

Optimization and Control · Mathematics 2023-01-16 David Martínez-Rubio

We give a lower bound for the Gaussian curvature of convex level sets of minimal graphs and the solutions to semilinear elliptic equations with the norm of boundary gradient and the Gaussian curvature of the boundary.

Analysis of PDEs · Mathematics 2010-03-11 Pei-He Wang , Wei Zhang

The Gaussian curvature of a two-dimensional Riemannian manifold is uniquely determined by the choice of the metric. The formulas for computing the curvature in terms of components of the metric, in isothermal coordinates, involve the…

Differential Geometry · Mathematics 2013-11-11 Haakan Hedenmalm , Yolanda Perdomo

For an oriented isometric immersion $f:M\to S^n$ the spherical Gauss map is the Legendrian immersion of its unit normal bundle $UM^\perp$ into the unit sphere subbundle of $TS^n$, and the geodesic Gauss map $\gamma$ projects this into the…

Differential Geometry · Mathematics 2015-04-29 Chris Draper , Ian McIntosh

We write down estimates for the surface area, and more generally, integral mean curvatures of an ellipsoid E in n-dimensional Euclidean space in terms of the lengths of the major semi-axes. We give applications to estimating the area of…

Metric Geometry · Mathematics 2007-05-23 Igor Rivin

In analogy with the study of Pollicott-Ruelle resonances on negatively curved manifolds, we define anisotropic Sobolev spaces that are well-adapted to the analysis of the geodesic vector field associated with any translation invariant…

Analysis of PDEs · Mathematics 2023-11-07 Nguyen Viet Dang , Matthieu Léautaud , Gabriel Rivière

The authors Balogh-Tyson-Vecchi in arXiv:1604.00180 utilize the Riemannian approximations scheme $(\mathbb H^1,<,>_L)$, in the Heisenberg group, introduced by Gromov, to calculate the limits of Gaussian and normal curvatures defined on…

Differential Geometry · Mathematics 2020-02-19 Jose Veloso

We derive a priori estimates for second order derivatives of solutions to a wide calss of fully nonlinear elliptic equations on Riemannian manifolds. The equations we consider naturally appear in geometric problems and other applications…

Analysis of PDEs · Mathematics 2014-01-30 Bo Guan , Heming Jiao

Seiberg-Witten theory leads to a delicate interplay between Riemannian geometry and smooth topology in dimension four. In particular, the scalar curvature of any metric must satisfy certain non-trivial estimates if the manifold in question…

Differential Geometry · Mathematics 2016-09-07 Claude LeBrun

Second derivative pinching estimates are proved for a class of elliptic and parabolic equations, including motion of hypersurfaces by curvature functions such as quotients of elementary symmetric functions of curvature. The estimates imply…

Differential Geometry · Mathematics 2007-05-23 Ben Andrews

We address the problem of fitting parametric curves on the Grassmann manifold for the purpose of intrinsic parametric regression. As customary in the literature, we start from the energy minimization formulation of linear least-squares in…

Computer Vision and Pattern Recognition · Computer Science 2015-05-15 Yi Hong , Nikhil Singh , Roland Kwitt , Nuno Vasconcelos , Marc Niethammer