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In this paper we study similarity measures for moving curves which can, for example, model changing coastlines or retreating glacier termini. Points on a moving curve have two parameters, namely the position along the curve as well as time.…

Computational Geometry · Computer Science 2015-07-15 Kevin Buchin , Tim Ophelders , Bettina Speckmann

We consider an analogue of the Kac random walk on the special orthogonal group $SO(N)$, in which at each step a random rotation is performed in a randomly chosen 2-plane of $\bR^N$. We obtain sharp asymptotics for the rate of convergence in…

Probability · Mathematics 2021-05-25 Bob Hough , Yunjiang Jiang

We give a short axiomatic introduction to Carnot groups and their subRiemannian and subFinsler geometry. We explain how such spaces can be metrically described as exactly those proper geodesic spaces that admit dilations and are…

Metric Geometry · Mathematics 2014-08-26 Enrico Le Donne

In this paper we study the notion of geodesic curvature of smooth horizontal curves parametrized by arc lenght in the Heisenberg group, that is the simplest sub-Riemannian structure. Our goal is to give a metric interpretation of this…

Differential Geometry · Mathematics 2019-02-28 Mathieu Kohli

We design a deterministic algorithm that, given $n$ points in a \emph{typical} constant degree regular~graph, queries $O(n)$ distances to output a constant factor approximation to the average distance among those points, thus answering a…

Data Structures and Algorithms · Computer Science 2025-10-22 Alexandros Eskenazis , Manor Mendel , Assaf Naor

An intrinsic definition in terms of conformal capacity is proposed for the conformal type of a Carnot--Carath\'eodory space (parabolic or hyperbolic). Geometric criteria of conformal type are presented. They are closely related to the…

Differential Geometry · Mathematics 2016-09-06 Vladimir A. Zorich

An approach to analysis on path spaces of Riemannian manifolds is described. The spaces are furnished with `Brownian motion' measure which lies on continuous paths, though differentiation is restricted to directions given by tangent paths…

Probability · Mathematics 2023-03-07 K. D. Elworthy , Xue-Mei Li

The Fr\'{e}chet distance is a well-studied similarity measure between curves that is widely used throughout computer science. Motivated by applications where curves stem from paths and walks on an underlying graph (such as a road network),…

Computational Geometry · Computer Science 2024-11-20 Anne Driemel , Ivor van der Hoog , Eva Rotenberg

Let $f: D \rightarrow \Omega$ be a complex analytic function. The Julia quotient is given by the ratio between the distance of $f(z)$ to the boundary of $\Omega$ and the distance of $z$ to the boundary of $D.$ A classical…

Functional Analysis · Mathematics 2018-09-26 J. E. Pascoe , Meredith Sargent , Ryan Tully-Doyle

The Hausdorff distance measures how far apart two sets are in a common metric space. By contrast, the Gromov-Hausdorff distance provides a notion of distance between two abstract metric spaces. How do these distances behave for quotients of…

We consider the defocusing nonlinear Schr\"odinger equations on the two-dimensional compact Riemannian manifold without boundary or a bounded domain in $\R^2$. Our aim is to give a pedagogic and self-contained presentation on the Wick…

Analysis of PDEs · Mathematics 2017-07-13 Tadahiro Oh , Laurent Thomann

This paper investigates the application of the classical Chernoff's theorem to construct explicit solutions for the heat and Schr\"odinger equations on the Heisenberg group $\mathbb{H}^d$. Using semigroup approximation techniques, we obtain…

Analysis of PDEs · Mathematics 2025-03-25 Nicolò Drago , Sonia Mazzucchi , Andrea Pinamonti

Geometric frameworks for analyzing curves are common in applications as they focus on invariant features and provide visually satisfying solutions to standard problems such as computing invariant distances, averaging curves, or registering…

Methodology · Statistics 2025-11-24 Perrine Chassat , Juhyun Park , Nicolas Brunel

Our main aim is to present a geometrically meaningful formula for the fundamental solutions to a second order sub-elliptic differential equation and to the heat equation associated with a sub-elliptic operator in the sub-Riemannian geometry…

Differential Geometry · Mathematics 2008-09-17 Der-Chen Chang , Irina Markina , Alexander Vasil'ev

Geodesics are used in a wide array of applications in cosmology and astrophysics. However, it is not a trivial task to efficiently calculate exact geodesic distances in an arbitrary spacetime. We show that in spatially flat…

General Relativity and Quantum Cosmology · Physics 2017-11-29 William J. Cunningham , David Rideout , James Halverson , Dmitri Krioukov

We study the dynamical behaviors of degenerate stochastic differential equations (SDEs). We select an auxiliary Fisher information functional as the Lyapunov functional. Using generalized Fisher information, we conduct the Lyapunov…

Differential Geometry · Mathematics 2023-05-15 Qi Feng , Wuchen Li

We show that the Heisenberg group is not minimal in looking down. This answers Problem 11.15 in `Fractured fractals and broken dreams' by David and Semmes, or equivalently, Question 22 and hence also Question 24 in `Thirty-three yes or no…

Metric Geometry · Mathematics 2015-08-26 Enrico Le Donne , Sean Li , Tapio Rajala

In order to study the quantum geometry of random surfaces in Liouville gravity, we propose a definition of geodesic distance associated to a Gaussian free field on a regular lattice. This geodesic distance is used to numerically determine…

High Energy Physics - Theory · Physics 2014-11-13 Jan Ambjorn , Timothy Budd

Given a fixed closed manifold M, we exhibit an explicit formula for the distance function of the canonical L^2 Riemannian metric on the manifold of all smooth Riemannian metrics on M. Additionally, we examine the (metric) completion of the…

Differential Geometry · Mathematics 2011-07-28 Brian Clarke

This work considers the problem of estimating the distance between two covariance matrices directly from the data. Particularly, we are interested in the family of distances that can be expressed as sums of traces of functions that are…

Machine Learning · Computer Science 2024-09-19 Roberto Pereira , Xavier Mestre , Davig Gregoratti