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We present a constructive approach for approximating the conformal map (uniformization) of a polyhedral surface to a canonical domain in the plane. The main tool is a characterization of convex spaces of quasiconformal simplicial maps and…

Computational Geometry · Computer Science 2013-01-29 Yaron Lipman

In the overview, a generic mathematical object (mapping) is introduced, and its relation to model physics parameterization is explained. Machine learning (ML) tools that can be used to emulate and/or approximate mappings are introduced.…

Atmospheric and Oceanic Physics · Physics 2022-06-22 Vladimir Krasnopolsky , Aleksei A. Belochitski

We study the synchronization properties of a generic networked dynamical system, and show that, under a suitable approximation, the transition to synchronization can be predicted with the only help of eigenvalues and eigenvectors of the…

In this paper, we aim to investigate the synchronization problem of dynamical systems, which can be of generic linear or Lipschitz nonlinear type, communicating over directed switching network topologies. A mild connectivity assumption on…

Systems and Control · Computer Science 2018-07-23 Jiahu Qin , Qichao Ma , Xinghuo Yu , Long Wang

We use mass-transportation as a tool to compare surfaces (2-manifolds). In particular, we determine the "similarity" of two given surfaces by solving a mass-transportation problem between their conformal densities. This mass transportation…

Numerical Analysis · Mathematics 2010-03-19 Y. Lipman , I. Daubechies

A general explicit coupling for mutual synchronization of two arbitrary identical continuous systems is proposed. The synchronization is proved analytically. The coupling is given for all 19 systems from Sprott's collection. For one of the…

Chaotic Dynamics · Physics 2009-11-11 A. I. Lerescu , S. Oancea , I. Grosu

Some properties of generalized convexity for sets and for functions are identified in case of the reliability polynomials of two dual minimal networks. A method of approximating the reliability polynomials of two dual minimal network is…

Discrete Mathematics · Computer Science 2021-12-14 Gabriela Cristescu , Vlad-Florin Dragoi , Sorin-Horatiu Hoara

We introduce a general definition of almost $p$-summing mappings and give several concrete examples of such mappings. Some known results are considerably generalized and we present various situations in which the space of almost $p$-summing…

Functional Analysis · Mathematics 2007-05-23 Daniel M. Pellegrino

The fusion of independently obtained stochastic maps by collaborating mobile agents is considered. The proposed approach includes two parts: matching of stochastic maps and maximum likelihood alignment. In particular, an affine invariant…

Applications · Statistics 2015-06-15 Brandon Jones , Mark Campbell , Lang Tong

The use of Laplacian eigenbases has been shown to be fruitful in many computer graphics applications. Today, state-of-the-art approaches to shape analysis, synthesis, and correspondence rely on these natural harmonic bases that allow using…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 A. Kovnatsky , M. M. Bronstein , A. M. Bronstein , K. Glashoff , R. Kimmel

Reflecting boundary conditions cause two one-dimensional random walks to synchronize if a common direction is chosen in each step. The mean synchronization time and its standard deviation are calculated analytically. Both quantities are…

Disordered Systems and Neural Networks · Physics 2007-05-23 Andreas Ruttor , Georg Reents , Wolfgang Kinzel

Neural manifolds summarize the intrinsic structure of the information encoded by a population of neurons. Advances in experimental techniques have made simultaneous recordings from multiple brain regions increasingly commonplace, raising…

Neurons and Cognition · Quantitative Biology 2025-03-27 Iris H. R. Yoon , Gregory Henselman-Petrusek , Yiyi Yu , Robert Ghrist , Spencer LaVere Smith , Chad Giusti

We present a technique for approximating generic normalization constants subject to constraints. The method is then applied to derive the exact asymptotics for the conditional normalization constant of constrained exponential random graphs.

Probability · Mathematics 2015-08-05 Mei Yin

We determine approximate numerical integrals of motion of 2D symmetric Hamiltonian systems. We detail for a few gravitational potentials the conditions under which quasi-integrals are obtained as polynomial series. We show that each of…

Astrophysics of Galaxies · Physics 2015-06-12 Olivier Bienaymé , Gregor Traven

We study the computation of local approximations of invariant manifolds of parabolic fixed points and parabolic periodic orbits of periodic vector fields. If the dimension of these manifolds is two or greater, in general, it is not possible…

Dynamical Systems · Mathematics 2016-03-09 Inmaculada Baldomá , Ernest Fontich , Pau Martín

Random invariant manifolds often provide geometric structures for understanding stochastic dynamics. In this paper, a dynamical approximation estimate is derived for a class of stochastic partial differential equations, by showing that the…

Dynamical Systems · Mathematics 2007-10-08 Wei Wang , Jinqiao Duan

Invariant manifolds of unstable periodic orbits organize the dynamics of chaotic orbits in phase space. They provide insight into the mechanisms of transport and chaotic advection and have important applications in physical situations…

Chaotic Dynamics · Physics 2018-01-25 D. Ciro , I. L. Caldas , R. L. Viana , T. E. Evans

Temporal graphs are commonly used to represent time-resolved relations between entities in many natural and artificial systems. Many techniques were devised to investigate the evolution of temporal graphs by comparing their state at…

Social and Information Networks · Computer Science 2024-11-20 Lorenzo Dall'Amico , Alain Barrat , Ciro Cattuto

There are many methods developed to approximate a cloud of vectors embedded in high-dimensional space by simpler objects: starting from principal points and linear manifolds to self-organizing maps, neural gas, elastic maps, various types…

Machine Learning · Statistics 2016-09-01 E. M. Mirkes , A. Zinovyev , A. N. Gorban

One of the very few mathematically rigorous nonlinear model reduction methods is the restriction of a dynamical system to a low-dimensional, sufficiently smooth, attracting invariant manifold. Such manifolds are usually found using local…

Dynamical Systems · Mathematics 2025-05-12 Bálint Kaszás , George Haller