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We derive a formula which is a lower bound on the dimension of trivariate splines on a tetrahedral partition which are continuously differentiable of order $r$ in large enough degree. While this formula may fail to be a lower bound on the…

Numerical Analysis · Mathematics 2020-07-27 Michael DiPasquale , Nelly Villamizar

The scalar fields of supersymmetric models are coordinates of a geometric space. We propose a formulation of supersymmetry that is covariant with respect to reparametrizations of this target space. Employing chiral multiplets as an example,…

High Energy Physics - Theory · Physics 2017-04-26 Daniel Z. Freedman , Diederik Roest , Antoine Van Proeyen

Complex geometric properties of the orbits of a non-compact real form $G_0$ in a flag manifold $Z=G/Q$ of a complex semi-simple groups $G=G_0^\mathbb C$ are studied. Schubert varieties are used to construct a complex submanifold with…

Algebraic Geometry · Mathematics 2007-05-23 A. Huckleberry , J. A. Wolf

A generalisation of Riemannian geometry is considered, based exclusively on the minimal assumptions that the line element $ds$ is a regular function of position and direction and that the distance of every point from itself is equal to…

General Physics · Physics 2018-04-03 Paolo Maraner

Let X be a symplectic or odd orthogonal Grassmannian which parametrizes isotropic subspaces in a vector space equipped with a nondegenerate (skew) symmetric form. We prove quantum Giambelli formulas which express an arbitrary Schubert class…

Algebraic Geometry · Mathematics 2008-12-05 Anders S. Buch , Andrew Kresch , Harry Tamvakis

We consider the continuous Fermat-Weber problem, where the customers are continuously (uniformly) distributed along the boundary of a convex polygon. We derive the closed-form expression for finding the average distance from a given point…

Computational Geometry · Computer Science 2014-03-18 Thomas T. C. K. Zhang , John Gunnar Carlsson

Considering a n-dimensional general spacetime, we deduce its 4-dimensional Einstein equation and Friedman equations, and discover a general dual relation between the scale factor $a(t)$ of our universe and the scale factor $B(t)$ of extra…

General Relativity and Quantum Cosmology · Physics 2015-01-20 Yong-Chang Huang , LiuJi Li

Distance Geometry is based on the inverse problem that asks to find the positions of points, in a Euclidean space of given dimension, that are compatible with a given set of distances. We briefly introduce the field, and discuss some open…

Metric Geometry · Mathematics 2016-10-04 Leo Liberti , Carlile Lavor

We provide an implementation to compute the flat metric in any dimension. The flat metric, also called dual bounded Lipschitz distance, generalizes the well-known Wasserstein distance $W_1$ to the case that the distributions are of unequal…

Machine Learning · Computer Science 2025-06-17 Henri Schmidt , Christian Düll

We introduce a theoretical framework for performing statistical tasks---including, but not limited to, averaging and principal component analysis---on the space of (possibly asymmetric) matrices with arbitrary entries and sizes. This is…

Metric Geometry · Mathematics 2020-04-24 Samir Chowdhury , Tom Needham

Let $Q$ be a quiver of extended Dynkin type $D$. In this first of two papers, we show that the quiver Grassmannian $Gr_e(M)$ has a decomposition into affine spaces for every dimension vector $e$ and every indecomposable representation $M$…

Representation Theory · Mathematics 2015-07-03 Oliver Lorscheid , Thorsten Weist

We apply the previous calculations of Chow-Witt rings of Grassmannians to develop an oriented analogue of the classical Schubert calculus. As a result, we get complete diagrammatic descriptions of the ring structure in Chow-Witt rings and…

Algebraic Geometry · Mathematics 2018-08-23 Matthias Wendt

We study the possibility of defining a distance on the whole space of measures, with the property that the distance between two measures having the same mass is the Wasserstein distance, up to a scaling factor. We prove that, under very…

Metric Geometry · Mathematics 2021-12-10 Luca Lombardini , Francesco Rossi

We propose a novel evolutionary algorithm for optimizing real-valued objective functions defined on the Grassmann manifold Gr}(k,n), the space of all k-dimensional linear subspaces of R^n. While existing optimization techniques on Gr}(k,n)…

Optimization and Control · Mathematics 2025-03-31 Andrew Lesniewski

In this paper, we discuss the embeddability of subspaces of the Gromov-Hausdorff space, which consists of isometry classes of compact metric spaces endowed with the Gromov-Hausdorff distance, into Hilbert spaces. These embeddings are…

Metric Geometry · Mathematics 2025-11-26 Nicolò Zava

We answer some questions related to multiplicity formulas by Rosenthal and Zelevinsky and by Lakshmibai and Weyman for points on Schubert varieties in Grassmannians. In particular, we give combinatorial interpretations in terms of…

Algebraic Geometry · Mathematics 2007-05-23 Christian Krattenthaler

We introduce the observable Wasserstein distance, a framework for deriving lower bounds on the Wasserstein distance between probability measures on Polish metric spaces, designed to bypass the computational intractability of exact optimal…

Metric Geometry · Mathematics 2026-05-12 Edivaldo Lopes dos Santos , Leandro Vicente Mauri , Washington Mio , Tom Needham

In the first part, we give a self contained introduction to the theory of cyclic systems in n-dimensional space which can be considered as immersions into certain Grassmannians. We show how the (metric) geometries on spaces of constant…

dg-ga · Mathematics 2008-02-03 U. Hertrich-Jeromin , E. -H. Tjaden , M. T. Zuercher

We give a dimensionality reduction procedure to approximate the sum of distances of a given set of $n$ points in $R^d$ to any "shape" that lies in a $k$-dimensional subspace. Here, by "shape" we mean any set of points in $R^d$. Our…

Data Structures and Algorithms · Computer Science 2021-06-25 Zhili Feng , Praneeth Kacham , David P. Woodruff

Dimension reduction techniques typically seek an embedding of a high-dimensional point cloud into a low-dimensional Euclidean space which optimally preserves the geometry of the input data. Based on expert knowledge, one may instead wish to…

Optimization and Control · Mathematics 2025-02-28 Ranthony A. Clark , Tom Needham , Thomas Weighill