Solve Beltrami problem in dimension two
arXiv research
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Recent work by physicists on gravity in two dimensions has a natural generalization to four dimensions, formulated in terms of an analogue of Segal's category [defined for the study of conformal field theory].
The study finds limits on dimensions of certain scales and fields for conformal manifolds.
Perimeter minimizers in curved spaces have a singular set no more than 5 dimensions.
We derive explicit, uniform, a priori interior Hessian and gradient estimates for special Lagrangian equations of all phases in dimension two.
We prove that there are just two types of isolated singularities of special Kähler metrics in real dimension two provided the associated holomorphic cubic form does not have essential singularities. We also construct examples of such metrics.
Two methods preserve tensor structure for reduced dimensionality in tensor regression.
Two-dimensional collapsed spaces with lower Ricci bounds are topological surfaces.
We show that the algebraic dimension of a twistor space over n#CP^2 cannot be two if n>4 and the fundamental system (i.e. the linear system associated to the half-anti-canonical bundle, which is available on any twistor space) is a pencil. This means that if the algebraic dimension of a twistor space on n#CP^2, n>4, is…
Study on elasticity with mixed boundary conditions, proving spectral asymptotics.
In higher dimensions, Schottky spaces have unique topological properties.
Sharp bound on singular set dimension for specific geometric problems.
New bounds on geodesic dimension and curvature exponent in Carnot groups.
In this paper, we introduce a framework of -flows on triangulated manifolds with two and three dimensions, which unifies several discrete curvature flows previously defined in the literature.
Bernstein theorem proven for 2-valued minimal graphs in 4D.
Study on kernel tests for high-dimensional data, focusing on MMD and CLT.
We study the topology of smectic defects in two and three dimensions. We give a topological classification of smectic point defects and disclination lines in three dimensions. In addition we describe the combination rules for smectic point defects in two and three dimensions, showing how the broken translational symmet…
Training neural networks is hard in fixed dimensions.
This work generalizes a geometric Laplacian determinant description to higher dimensions.
In this paper we provide a criteria for geometric finiteness of Kleinian groups in general dimension. We formulate the concept of conformal finiteness for Kleinian groups in space of dimension higher than two, which generalizes the notion of analytic finiteness in dimension two. Then we extend the argument in the paper…
The approximability of a convex body is a number which measures the difficulty to approximate that body by polytopes. We prove that twice the approximability is equal to the volume entropy for a Hilbert geometry in dimension two end three and that in higher dimension it is a lower bound of the entropy. As a corollary w…
New findings on embedding simplicial complexes, showing instability under joins.
We obtain some improved essentially sharp Kakeya-Nikodym estimates for eigenfunctions in two-dimensions. We obtain these by proving stronger related microlocal estimates involving a natural decomposition of phase space that is adapted to the geodesic flow.
In this paper, we prove that given two cubical links of dimension two in , they are isotopic if and only if one can pass from one to the other by a finite sequence of cubulated moves. These moves are analogous to the Reidemeister and Roseman moves for classical tame knots of dimension one and two, respec…
We present local estimates for solutions to the Ricci flow, without the assumption that the solution has bounded curvature. These estimates lead to a generalisation of one of the pseudolocality results of G.Perelman in dimension two.
We prove that in two dimensions the synthetic notions of lower bounds on sectional and on Ricci curvature coincide.
In this paper we give a re-normalization of the Reshetikhin-Turaev quantum invariants of links, by modified quantum dimensions. In the case of simple Lie algebras these modified quantum dimensions are proportional to the usual quantum dimensions. More interestingly we will give two examples where the usual quantum dime…
We study piecewise linear co-dimension two embeddings of closed oriented manifolds in Euclidean space, and show that any such embedding can always be isotoped to be a closed braid as long as the ambient dimension is at most five, extending results of Alexander (in ambient dimension three), and Viro and independently Ka…
Two-root Riemannian manifolds have no odd-dimensional examples.
Surveying mass in 2D hyperbolic geometry, overcoming challenges via minimisation.
We proof that in dimension two, a Finsler metric is Douglas and generalized Berwald, if and only if it is Berwald or a Randers metric , where is closed and is of constant length with respect to .
In this article, we consider the rolling (or development) of two Riemannian connected manifolds and of dimensions and respectively, with the constraints of no-spinning and no-slipping. The present work is a continuation of \cite{MortadaKokkonenChitour}, which modelled the general set…
Investigates maps and properties in spaces with negative dimensions and curvature.
Contradiction graphs reveal VC dimension threshold.
In the first part of the paper we show how to relate several dimension theories (asymptotic dimension with Higson property, asymptotic dimension of Gromov, and capacity dimension of Buyalo \cite{Buyalo1}) to Nagata-Assouad dimension. This is done by applying two functors on the Lipschitz category of metric spaces: micr…
The study examines non-Kähler threefolds with specific metrics and finds they are quasi-bundles over surfaces.
The asymptotic dimension theory was founded by Gromov in the early 90s. In this paper we give a survey of its recent history where we emphasize two of its features: an analogy with the dimension theory of compact metric spaces and applications to the theory of discrete groups.
It is proved that a compact Kahler manifold whose Ricci tensor has two distinct, constant, non-negative eigenvalues is locally the product of two Kahler-Einstein manifolds. A stronger result is established for the case of Kahler surfaces. Irreducible Kahler manifolds with two distinct, constant eigenvalues of the Ricci…
The paper explores Kähler-Ricci solitons with maximal symmetry in complex dimension two.
DSNE visualizes data velocity in lower dimensions.
Connected sums defined for codimension two locally flat submanifolds in higher dimensions.
The paper extends results on minimal hypersurfaces in Riemannian manifolds to higher dimensions.
Generalizing previous work by two of us, we prove the non-existence of certain stationary configurations in General Relativity having a spatial reflection symmetry across a non-compact surface disjoint from the matter region. Our results cover cases such that of two symmetrically arranged rotating bodies with anti-alig…
Random feature matrices' singular values concentrate near their full expectation in high dimensions.
A recent anomaly computation of Horava and Witten is proved and generalized in the form of two index theorems in odd dimensions. Theorem A is a fixed point formula for orientation-reversing involutions. Theorem B is an index theorem for manifolds with boundary using local boundary conditions. Both hold for families of …
A method, due to Élie Cartan, is used to give an algebraic classification of the non-reductive homogeneous pseudo-Riemannian manifolds of dimension four. Only one case with Lorentz signature can be Einstein without having constant curvature, and two cases with (2,2) signature are Einstein of which one is Ricci-flat. If…
We construct local models of isolated singularities for special Kähler structures in real dimension two assuming that the associated holomorphic cubic form does not have essential singularities. As an application we compute the holonomy of the flat symplectic connection, which is a part of the special Kähler structure.
t-SNE is a popular tool for embedding multi-dimensional datasets into two or three dimensions. However, it has a large computational cost, especially when the input data has many dimensions. Many use t-SNE to embed the output of a neural network, which is generally of much lower dimension than the original data. This l…