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We study the space of oriented genus g subsurfaces of a fixed manifold M, and in particular its homological properties. We construct a "scanning map" which compares this space to the space of sections of a certain fibre bundle over M…

Algebraic Topology · Mathematics 2017-06-14 Federico Cantero Morán , Oscar Randal-Williams

In my talk I will discuss the following results which were obtained in joint work with Wilderich Tuschmann. 1. For any given numbers $m$, $C$ and $D$, the class of $m$-dimensional simply connected closed smooth manifolds with finite second…

Differential Geometry · Mathematics 2007-05-23 Anton Petrunin

Recently, the theory of diffusion maps was extended to a large class of local kernels with exponential decay which were shown to represent various Riemannian geometries on a data set sampled from a manifold embedded in Euclidean space.…

Classical Analysis and ODEs · Mathematics 2015-09-28 Tyrus Berry , John Harlim

An involutive diffeomorphism $\sigma$ of a connected smooth manifold $M$ is called dissecting if the complement of its fixed point set is not connected. Dissecting involutions on a complete Riemannian manifold are closely related to…

Differential Geometry · Mathematics 2019-12-20 Karl-Hermann Neeb , Gestur Olafsson

We prove rigidity results describing contextually-constrained maps defined on Grassmannians and manifolds of ordered independent line tuples in finite-dimensional vector or Hilbert spaces. One statement in the spirit of the Fundamental…

Functional Analysis · Mathematics 2026-01-21 Alexandru Chirvasitu

Embedding methods for product spaces are powerful techniques for low-distortion and low-dimensional representation of complex data structures. Here, we address the new problem of linear classification in product space forms -- products of…

Machine Learning · Computer Science 2022-01-04 Puoya Tabaghi , Chao Pan , Eli Chien , Jianhao Peng , Olgica Milenkovic

We study geometric and algebraic geometric properties of the continuous and discrete Neumann systems on cotangent bundles of Stiefel varieties $V_{n,r}$. The systems are integrable in the non-commutative sense, and by applying a $2r\times…

Exactly Solvable and Integrable Systems · Physics 2018-01-30 Yuri N. Fedorov , Bozidar Jovanovic

Around 1960, R. Palais and J. Cerf proved a fundamental result relating spaces of diffeomorphisms and imbeddings of manifolds: If V is a submanifold of M, then the map from Diff(M) to Imb(V,M) that takes f to its restriction to V is locally…

Geometric Topology · Mathematics 2007-05-23 John Kalliongis , Darryl McCullough

In the homotopical study of spaces of smooth embeddings, the functor calculus method (Goodwillie-Klein-Weiss manifold calculus) has opened up important connections to operad theory. Using this and a few simplifying observations, we arrive…

Algebraic Topology · Mathematics 2018-02-21 Pedro Boavida de Brito , Michael S. Weiss

A function from configuration space to moduli space of surface may induce a homomorphism between their fundamental groups which are braid groups and mapping class groups of surface, respectively. This map $\phi: B_k \rightarrow…

Algebraic Topology · Mathematics 2018-02-05 Byung Chun Kim , Yongjin Song

A Riemann-Cartan manifold is a Riemannian manifold endowed with an affine connection which is compatible with the metric tensor. This affine connection is not necessarily torsion free. Under the assumption that the manifold is a homogeneous…

Differential Geometry · Mathematics 2019-09-04 Cristina Draper , Antonio Garvín , Francisco J. Palomo

We give an approach for relative and degenerate Gromov--Witten invariants, inspired by that of Jun Li but replacing predeformable maps by transversal maps to a twisted target. The main advantage is a significant simplification in the…

Algebraic Geometry · Mathematics 2014-08-06 Dan Abramovich , Barbara Fantechi

We study approximation of probability measures supported on $n$-dimensional manifolds embedded in $\mathbb{R}^m$ by injective flows -- neural networks composed of invertible flows and injective layers. We show that in general, injective…

Machine Learning · Computer Science 2022-06-28 Michael Puthawala , Matti Lassas , Ivan Dokmanić , Maarten de Hoop

We prove for the first time a pointwise lower estimate of the normal injectivity radius of an embedded hypersurface in an arbitrary Riemannian manifold. Main applications include: (i) a pointwise lower estimate of the graphing radius of a…

Differential Geometry · Mathematics 2025-11-26 Sebastian Boldt , Batu Güneysu , Stefano Pigola

Let A be an m-dimensional vector with positive real entries. Let A_{i,j} be the vector obtained from A on deleting the entries A_i and A_j. We investigate some invariant and near invariants related to the solutions E (m-2 dimensional…

Rings and Algebras · Mathematics 2007-05-23 Amnon Besser , Pieter Moree

We investigate point arrangements $v_i\in\mathbb R^d,i\in \{1,...,n \}$ with certain prescribed symmetries. The arrangement space of $v$ is the column span of the matrix in which the $v_i$ are the rows. We characterize properties of $v$ in…

Metric Geometry · Mathematics 2021-03-02 Martin Winter

In this paper we show that if one writes down the structure equations for the evolution of a curve embedded in an (n)-dimensional Riemannian manifold with constant curvature this leads to a symplectic, a Hamiltonian and an hereditary…

Analysis of PDEs · Mathematics 2007-05-23 Jan A. Sanders , Jing Ping Wang

We study the Disc-structure space $S^{\rm Disc}_\partial(M)$ of a compact smooth manifold $M$. Informally speaking, this space measures the difference between $M$, together with its diffeomorphisms, and the diagram of ordered framed…

Algebraic Topology · Mathematics 2024-12-18 Manuel Krannich , Alexander Kupers

Finite-order invariants of knots in arbitrary 3-manifolds (including non-orientable ones) are constructed and studied by methods of the topology of discriminant sets. Obstructions to the integrability of admissible weight systems to…

Geometric Topology · Mathematics 2016-09-07 Victor A. Vassiliev

Many techniques in machine learning attempt explicitly or implicitly to infer a low-dimensional manifold structure of an underlying physical phenomenon from measurements without an explicit model of the phenomenon or the measurement…

Machine Learning · Statistics 2023-07-04 Roy R. Lederman , Bogdan Toader