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Mechanical fields over thin elastic surfaces can develop singularities at isolated points and curves in response to constrained deformations (e.g., crumpling and folding of paper), singular body forces and couples, distributions of isolated…

Mathematical Physics · Physics 2022-08-17 Animesh Pandey , Anurag Gupta

Optical singularities, which are positions within an electromagnetic field where certain field parameters become undefined, hold significant potential for applications in areas such as super-resolution microscopy, sensing, and…

We investigate geometric properties of surfaces given by certain formulae. In particular, we calculate the singular curvature and the limiting normal curvature of such surfaces along the set of singular points consisting of singular points…

Differential Geometry · Mathematics 2020-03-25 Yoshiki Matsushita , Takuya Nakashima , Keisuke Teramoto

In this paper, using the similarity method, we construct particular solutions with singularities for degenerate high-order equations. The considered equations have singularities of the first and second kind. Particular solutions are…

Analysis of PDEs · Mathematics 2020-05-06 B. Yu. Irgashev

A rather complete phenomenology of the singularities is developed according to a new algebraic point of view in the frame of Langlands global correspondences. That is to say,a process of: -singularizations and versal deformations of these,…

Representation Theory · Mathematics 2007-05-23 Christian Pierre

Factorized spectral surface scenario has been considered as one of solutions to the dimension-4 proton decay problem in supersymmetric compactifications of F-theory. It has been formulated in language of gauge theory on 7+1 dimensions, but…

High Energy Physics - Theory · Physics 2014-11-20 Hirotaka Hayashi , Teruhiko Kawano , Yoichi Tsuchiya , Taizan Watari

The aim of the article is to recover a certain type of finite parametric distributions and functions using their spherical mean transform which is given on a certain family of spheres whose centers belong to a finite set $\Gamma$. For this,…

Analysis of PDEs · Mathematics 2016-11-01 Yehonatan Salman

The conjugate function method is an algorithm for numerical computation of conformal mappings for simply and multiply connected domains on surfaces. In this paper the conjugate function method, earlier used for simply connected domains, is…

Numerical Analysis · Mathematics 2026-05-26 H. Hakula , A. Rasila , Y. Zheng

In the finite dimensional case, mean-type mappings, their invariant means, relations between the uniqueness of invariant means and convergence of orbits of the mapping, are considered. In particular it is shown, that the uniqueness of an…

Classical Analysis and ODEs · Mathematics 2022-06-10 Janusz Matkowski , Paweł Pasteczka

We are concerned with a class of nonconvex and nonsmooth composite optimization problems, comprising a twice differentiable function and a prox-regular function. We establish a sufficient condition for the proximal mapping of a prox-regular…

Optimization and Control · Mathematics 2025-09-09 Yuqia Wu , Pengcheng Wu , Yaohua Hu , Shaohua Pan , Xiaoqi Yang

In this paper, we consider deformations of singular complex curves on complex surfaces. Despite the fundamental nature of the problem, little seems to be known for curves on general surfaces. Let $C\subset S$ be a complete integral curve on…

Algebraic Geometry · Mathematics 2023-10-24 Takeo Nishinou

Spectral measures arise in numerous applications such as quantum mechanics, signal processing, resonances, and fluid stability. Similarly, spectral decompositions (pure point, absolutely continuous and singular continuous) often…

Spectral Theory · Mathematics 2021-03-02 Matthew John Colbrook

We study an inverse spectral problem for arbitrary order ordinary differential equations on compact star-type graphs when differential equations have regular singularities at boundary vertices. As the main spectral characteristics we…

Spectral Theory · Mathematics 2014-10-09 Vjacheslav Yurko

Mirror-prox (MP) is a well-known algorithm to solve variational inequality (VI) problems. VI with a monotone operator covers a large group of settings such as convex minimization, min-max or saddle point problems. To get a convergent…

Machine Learning · Computer Science 2020-11-24 Reza Babanezhad , Simon Lacoste-Julien

The main problem studied is resolution of singularities of the cotangent sheaf of a complex- or real-analytic variety Y (or of an algebraic variety Y over a field of characteristic zero). Given Y, we ask whether there is a global resolution…

Algebraic Geometry · Mathematics 2015-11-09 Andre Belotto da Silva , Edward Bierstone , Vincent Grandjean , Pierre D. Milman

We study inverse spectral problems for ordinary differential equations with regular singularities on compact star-type graphs when differential equations have different orders on diferent edges. As the main spectral characteristics we…

Spectral Theory · Mathematics 2015-03-06 Vjacheslav Yurko

General factors are a generalization of matchings. Given a graph $G$ with a set $\pi(v)$ of feasible degrees, called a degree constraint, for each vertex $v$ of $G$, the general factor problem is to find a (spanning) subgraph $F$ of $G$…

Discrete Mathematics · Computer Science 2024-05-24 Shuai Shao , Stanislav Živný

Many parametrization and mapping-related problems in geometry processing can be viewed as metric optimization problems, i.e., computing a metric minimizing a functional and satisfying a set of constraints, such as flatness. Penner…

Computational Geometry · Computer Science 2024-03-06 Ryan Capouellez , Denis Zorin

In 1970s, a method was developed for integration of nonlinear equations by means of algebraic geometry. Starting from a Lax representation with spectral parameter, the algebro-geometric method allows to solve the system explicitly in terms…

Exactly Solvable and Integrable Systems · Physics 2016-08-10 Anton Izosimov

When analyzing parametric statistical models, a useful approach consists in modeling geometrically the parameter space. However, even for very simple and commonly used hierarchical models like statistical mixtures or stochastic deep neural…

Machine Learning · Computer Science 2021-12-08 Pascal Mattia Esser , Frank Nielsen
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