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We provide an easy approach to the geodesic distance on the general linear group GL(n) for left-invariant Riemannian metrics which are also right-O(n)-invariant. The parametrization of geodesic curves and the global existence of length…

Differential Geometry · Mathematics 2016-02-18 Robert Martin , Patrizio Neff

The paper is a study of geodesic in two-dimensional pseudo-Riemannian metrics. Firstly, the local properties of geodesics in a neighborhood of generic parabolic points are investigated. The equation of the geodesic flow has singularities at…

Differential Geometry · Mathematics 2016-11-22 Alexey Remizov

We introduce a novel formulation for geometry on discrete points. It is based on a universal differential calculus, which gives a geometric description of a discrete set by the algebra of functions. We expand this mathematical framework so…

Mathematical Physics · Physics 2020-02-11 Yuuya Takayama

A particular family of Discrete Time Quantum Walks (DTQWs) simulating fermion propagation in $2$D curved space-time is revisited. Usual continuous covariant derivatives and spin-connections are generalized into discrete covariant…

Quantum Physics · Physics 2019-03-01 Fabrice Debbasch

Finding appropriate notions of discrete holomorphic maps and, more generally, conformal immersions of discrete Riemann surfaces into 3-space is an important problem of discrete differential geometry and computer visualization. We propose an…

Differential Geometry · Mathematics 2012-12-21 Christoph Bohle , Franz Pedit , Ulrich Pinkall

Let $V$ be a separable Hilbert space, possibly infinite dimensional. Let $\St(p,V)$ be the Stiefel manifold of orthonormal frames of $p$ vectors in $V$, and let $\Gr(p,V)$ be the Grassmann manifold of $p$ dimensional subspaces of $V$. We…

Differential Geometry · Mathematics 2018-09-28 Philipp Harms , Andrea C. G. Mennucci

This paper proposes a new framework and algorithms to address the problem of diffeomorphic registration on a general class of geometric objects that can be described as discrete distributions of local direction vectors. It builds on both…

Optimization and Control · Mathematics 2018-02-15 Hsi-Wei Hsieh , Nicolas Charon

This paper is part of a program to combine a staggered time and staggered spatial discretization of continuum wave equations so that important properties of the continuum that are proved using vector calculus can be proven in an analogous…

Numerical Analysis · Mathematics 2020-10-13 Stanly Steinberg

The Large Deformation Diffeomorphic Metric Mapping (LDDMM) or flow of diffeomorphism is a classical framework in the field of shape spaces and is widely applied in mathematical imaging and computational anatomy. Essentially, it equips a…

Numerical Analysis · Mathematics 2026-02-27 Benedikt Wirth

We derive a continuum model for incompatible elasticity as a variational limit of a family of discrete nearest-neighbor elastic models. The discrete models are based on discretizations of a smooth Riemannian manifold $(M,\mathfrak{g})$,…

Analysis of PDEs · Mathematics 2019-01-23 Raz Kupferman , Cy Maor

We consider the fundamental task of optimising a real-valued function defined in a potentially high-dimensional Euclidean space, such as the loss function in many machine-learning tasks or the logarithm of the probability distribution in…

Machine Learning · Statistics 2024-03-20 Marcelo Hartmann , Bernardo Williams , Hanlin Yu , Mark Girolami , Alessandro Barp , Arto Klami

This monograph resolves - in a dense class of cases - several open problems concerning geodesics in i.i.d. first-passage percolation on $\mathbb{Z}^d$. Our primary interest is in the empirical measures of edge-weights observed along…

Probability · Mathematics 2021-10-04 Erik Bates

Group lattices (Cayley digraphs) of a discrete group are in natural correspondence with differential calculi on the group. On such a differential calculus geometric structures can be introduced following general recipes of noncommutative…

Mathematical Physics · Physics 2015-06-26 Aristophanes Dimakis , Folkert Muller-Hoissen

The length of the geodesic between two data points along a Riemannian manifold, induced by a deep generative model, yields a principled measure of similarity. Current approaches are limited to low-dimensional latent spaces, due to the…

A discretisation of differential geometry using the Whitney forms of algebraic topology is consistently extended via the introduction of a pairing on the space of chains. This pairing of chains enables us to give a definition of the…

High Energy Physics - Theory · Physics 2007-05-23 Vivien de Beauce , Siddhartha Sen

In this work we study the general system of geodesic equations for the case of a massive particle moving on an arbitrary curved manifold. The investigation is carried out from the symmetry perspective. By exploiting the parametrization…

General Relativity and Quantum Cosmology · Physics 2019-06-05 N. Dimakis , Petros A. Terzis , T. Christodoulakis

Several physical problems such as the `twin paradox' in curved spacetimes have purely geometrical nature and may be reduced to studying properties of bundles of timelike geodesics. The paper is a general introduction to systematic…

General Relativity and Quantum Cosmology · Physics 2015-07-10 Leszek M. Sokołowski , Zdzisław A. Golda

In this article, we investigate when the set of primitive geodesic lengths on a Riemannian manifold have arbitrarily long arithmetic progressions. We prove that in the space of negatively curved metrics, a metric having such arithmetic…

Differential Geometry · Mathematics 2018-12-24 Jean-François Lafont , D. B. McReynolds

A discretisation scheme that preserves topological features of a physical problem is extended so that differential geometric structures can be approximated in a consistent way thus giving access to the study of physical systems which are…

High Energy Physics - Theory · Physics 2007-05-23 Vivien de Beauce , Siddhartha Sen

Latent variable models are powerful tools for learning low-dimensional manifolds from high-dimensional data. However, when dealing with constrained data such as unit-norm vectors or symmetric positive-definite matrices, existing approaches…

Machine Learning · Computer Science 2025-03-10 Leonel Rozo , Miguel González-Duque , Noémie Jaquier , Søren Hauberg