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We study the problem of decomposition (non-commutative factorization) of linear ordinary differential operators near an irregular singular point. The solution (given in terms of the Newton diagram and the respective characteristic numbers)…

Classical Analysis and ODEs · Mathematics 2018-05-08 Leanne Mezuman , Sergei Yakovenko

We present the first steps of a procedure which discretises surface theory in classical projective differential geometry in such a manner that underlying integrable structure is preserved. We propose a canonical frame in terms of which the…

Differential Geometry · Mathematics 2018-07-04 W. K. Schief , A. Szereszewski

Results of number of geometric operations (often used in technical practise, as e.g. the operation of blending) are in many cases surfaces described implicitly. Then it is a challenging task to recognize the type of the obtained surface,…

Symbolic Computation · Computer Science 2014-07-11 Jan Vršek , Miroslav Lávička

Oriented normals are common pre-requisites for many geometric algorithms based on point clouds, such as Poisson surface reconstruction. However, it is not trivial to obtain a consistent orientation. In this work, we bridge orientation and…

Graphics · Computer Science 2023-05-02 Dong Xiao , Zuoqiang Shi , Siyu Li , Bailin Deng , Bin Wang

We study bipartite maps on the plane with one infinite face and one face of perimeter 2. At first we consider the problem of their enumeration an then study the connection between the combinatorial structure of a map and the degree of its…

Combinatorics · Mathematics 2017-06-30 Yury Kochetkov

It was recently shown that under mild assumptions second-order conformally superintegrable systems can be encoded in a $(0,3)$-tensor, called structure tensor. For abundant systems, this approach led to algebraic integrability conditions…

Differential Geometry · Mathematics 2025-04-08 Vicente Cortés , Andreas Vollmer

We use a new method to give conditions for the existence of a local isometric immersion of a Riemannian $n$-manifold $M$ in $\mathbb{R}^{n+k}$, for a given $n$ and $k$. These equate to the (local) existence of a $k$-tuple of scalar fields…

Differential Geometry · Mathematics 2019-09-02 Dan Gregorian Fodor

The integration of surface normals for the purpose of computing the shape of a surface in 3D space is a classic problem in computer vision. However, even nowadays it is still a challenging task to devise a method that combines the…

Numerical Analysis · Computer Science 2016-10-20 Martin Bähr , Michael Breuß , Yvain Quéau , Ali Sharifi Boroujerdi , Jean-Denis Durou

Given a $4$-dimensional vector subspace $U=\{ f_{0},\ldots,f_{3}\}$ of $H^{0}(\mathbb{P}^1 \times \mathbb{P}^1,\mathcal{O}(a,b))$, a tensor product surface, denoted by $X_{U}$, is the closure of the image of the rational map…

Commutative Algebra · Mathematics 2016-10-13 Eliana Duarte

We present an extension of an algorithm for the classical scalar $p$-Laplace Dirichlet problem to the vector-valued $p$-Laplacian with mixed boundary conditions in order to solve problems occurring in shape optimization using a $p$-harmonic…

Optimization and Control · Mathematics 2022-08-16 Henrik Wyschka , Martin Siebenborn

Let $\varphi:\mathbb{P}^1(\mathbb F_q)\to\mathbb{P}^1(\mathbb F_q)$ be a rational map of degree $d>1$ on a fixed finite field. We give asymptotic formulas for the size of image sets $\varphi^n(\mathbb{P}^1(\mathbb F_q))$ as a function of…

Number Theory · Mathematics 2019-11-07 Jamie Juul

We extend the shell and kernel reductions for hyperexponential functions over the field of rational functions to a monomial extension. Both of the reductions are incorporated into one algorithm. As an application, we present an additive…

Symbolic Computation · Computer Science 2023-10-03 Shaoshi Chen , Hao Du , Yiman Gao , Ziming Li

We derive an implicit description of the image of a semialgebraic set under a birational map, provided that the denominators of the map are positive on the set. For statistical models which are globally rationally identifiable, this yields…

Statistics Theory · Mathematics 2024-10-31 Tobias Boege , Liam Solus

An intrinsic description of the Hamilton-Cartan formalism for first-order Berezinian variational problems determined by a submersion of supermanifolds is given. This is achieved by studying the associated higher-order graded variational…

Mathematical Physics · Physics 2018-05-29 Juan Monterde , Jaime Muñoz-Masqué , José Antonio Vallejo

We consider closed and orientable immersed hypersurfaces of translational manifolds. Given a vector field on such a hypersurface, we define a perturbation of its Gauss map, which allows us to obtain topological invariants for the immersion…

Differential Geometry · Mathematics 2017-12-01 Ícaro Gonçalves , Eduardo Longa

We introduce a constructive method that provides the local solution of general implicit systems in arbitrary dimension via Hamiltonian type equations. A variant of this approach constructs parametrizations of the manifold, extending the…

Classical Analysis and ODEs · Mathematics 2019-09-18 Dan Tiba

The globalization problem arises when local tensor fields possess a given property (such as being symplectic or Poisson) but cannot be consistently extended to a global object due to incompatibilities on chart overlaps. A notable instance…

Differential Geometry · Mathematics 2026-01-14 Begüm Ateşli , Aybike Çatal-Özer

A kind of spatial fractional diffusion equations in this paper are studied. Firstly, an L1 formula is employed for the spatial discretization of the equations. Then, a second order scheme is derived based on the resulting semi-discrete…

Numerical Analysis · Mathematics 2020-01-08 Yong-Liang Zhao , Pei-Yong Zhu , Xian-Ming Gu , Xi-Le Zhao , Huan-Yan Jian

Kontsevich's formula for a deformation quantization of Poisson structures involves a Feynman series of graphs, with the weights given by some complicated integrals (using certain pullbacks of the standard angle form on a circe). We explain…

Geometric Topology · Mathematics 2009-11-07 Michael Polyak

Bayesian methods to solve imaging inverse problems usually combine an explicit data likelihood function with a prior distribution that explicitly models expected properties of the solution. Many kinds of priors have been explored in the…

Machine Learning · Statistics 2025-02-04 Rémi Laumont , Valentin de Bortoli , Andrés Almansa , Julie Delon , Alain Durmus , Marcelo Pereyra