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Modern, inherently dynamic systems are usually characterized by a network structure, i.e. an underlying graph topology, which is subject to discrete changes over time. Given a static underlying graph $G$, a temporal graph can be represented…

Computational Complexity · Computer Science 2019-08-13 Eleni C. Akrida , George B. Mertzios , Paul G. Spirakis , Viktor Zamaraev

Flows of vector fields are an essential tool in differential geometry, with countless applications in both theory and practice. While they have been extensively studied for ordinary manifolds and supermanifolds, a treatment of flows in…

Differential Geometry · Mathematics 2026-05-25 Rudolf Smolka , Jan Vysoky

We aim to completely formalize the rough topological analysis of integrable Hamiltonian systems admitting analytical solutions such that the initial phase variables along with the time derivatives of the auxiliary variables are expressed as…

Exactly Solvable and Integrable Systems · Physics 2013-09-30 Mikhail P. Kharlamov

Holomorphic functions are amazing because their values in an ever so small disk in the complex plane completely determine the function values at arbitrary points in their maximum possible domain. The process of extending such a function…

Complex Variables · Mathematics 2015-05-15 Stefan Kranich

Gaussian random fields with Mat\'ern covariance functions are popular models in spatial statistics and machine learning. In this work, we develop a spatio-temporal extension of the Gaussian Mat\'ern fields formulated as solutions to a…

Methodology · Statistics 2023-04-06 Finn Lindgren , Haakon Bakka , David Bolin , Elias Krainski , Håvard Rue

A study of proper conformal vector field in non conformally flat cylindrically symmetric static space-times is given by using direct integration technique. Using the above mentioned technique we have shown that a very special class of the…

General Relativity and Quantum Cosmology · Physics 2007-11-09 Ghulam Shabbir , Shaukat Iqbal

One approach to understanding complex data is to study its shape through the lens of algebraic topology. While the early development of topological data analysis focused primarily on static data, in recent years, theoretical and applied…

Machine Learning · Computer Science 2021-06-29 Lu Xian , Henry Adams , Chad M. Topaz , Lori Ziegelmeier

The aim of this work is to establish the existence of invariant manifolds in complex systems. Considering trajectory curves integral of multiple time scales dynamical systems of dimension two and three (predator-prey models, neuronal…

Dynamical Systems · Mathematics 2014-08-19 Jean-Marc Ginoux , Bruno Rossetto

Monotone vector fields were introduced almost 40 years ago as nonlinear extensions of positive definite linear operators, but also as natural extensions of gradients of convex potentials. These vector fields are not always derived from…

Analysis of PDEs · Mathematics 2008-04-02 Nassif Ghoussoub

Indices of vector fields on (complex analytic) singular varieties have been considered by various authors from several different viewpoints. All these indices coincide with the classical local index of Poincar\'e-Hopf when the ambient…

Algebraic Geometry · Mathematics 2007-05-23 Jose Seade

Graph models provide efficient tools to capture the underlying structure of data defined over networks. Many real-world network topologies are subject to change over time. Learning to model the dynamic interactions between entities in such…

Machine Learning · Computer Science 2025-01-03 Amirhossein Javaheri , Jiaxi Ying , Daniel P. Palomar , Farokh Marvasti

Most of the theoretical results on the kinematic amplification of small-scale magnetic fluctuations by turbulence have been confined to the model of white-noise-like advecting turbulent velocity field. In this work, the statistics of the…

Astrophysics · Physics 2009-10-31 Alexander Schekochihin , Russell Kulsrud

Scalar features in time-dependent fluid flow are traditionally visualized using 3D representation, and their topology changes over time are often conveyed with abstract graphs. Using such techniques, however, the structural details of…

This paper endeavors to learn time-varying graphs by using structured temporal priors that assume underlying relations between arbitrary two graphs in the graph sequence. Different from many existing chain structure based methods in which…

Machine Learning · Computer Science 2022-02-24 Xiang Zhang , Qiao Wang

For any arbitrary algebraic curve, we define an infinite sequence of invariants. We study their properties, in particular their variation under a variation of the curve, and their modular properties. We also study their limits when the…

Mathematical Physics · Physics 2007-05-23 Bertrand Eynard , Nicolas Orantin

We introduce time-periodic Gevrey-Sobolev-Kato spaces on asymptotically Euclidean manifolds and study their characterisation throughout Fourier expansions associated with suitable elliptic operators. As an application, we study the global…

Analysis of PDEs · Mathematics 2025-09-05 Fernando de Ávila Silva , Matteo Bonino , Sandro Coriasco

On the basis of the canonical quantization procedure of a system defined on a cubic lattice, we propose a new method, in which resolutions of unity expressed in terms of eigenvectors are naturally provided, to find eigenvectors of field…

High Energy Physics - Theory · Physics 2019-12-06 Seiji Sakoda

The continuity, in a suitable topology, of algebraic and geometric operations on real analytic manifolds and vector bundles is proved. This is carried out using recently arrived at seminorms for the real analytic topology. A new…

Differential Geometry · Mathematics 2022-02-15 Andrew D. Lewis

Based on a unique waveform with strong exponential localization property, an exact mathematical method for solving problems in signal analysis in time-frequency domain is presented. An analogue of the Gabor frame exposes the non-commutative…

Mathematical Physics · Physics 2012-06-12 Aramazd H. Muzhikyan , Gagik T. Avanesyan

The family of visibility algorithms were recently introduced as mappings between time series and graphs. Here we extend this method to characterize spatially extended data structures by mapping scalar fields of arbitrary dimension into…

Data Analysis, Statistics and Probability · Physics 2017-09-13 Lucas Lacasa , Jacopo Iacovacci