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We reconsider both the global and local stability of solutions of continuously evolving dynamical systems from a geometric perspective. We clarify that an unambiguous definition of stability generally requires the choice of additional…

Mathematical Physics · Physics 2009-08-12 Raffaele Punzi , Mattias N. R. Wohlfarth

The objective of this paper is to derive the essential invariance and contraction properties for the geometric periodic systems, which can be formulated as a category of differential inclusions, and primarily rendered in the phase…

Systems and Control · Electrical Eng. & Systems 2021-04-30 Chen Qian , Yongchun Fang

We present efficient algorithms for detecting central and mirror symmetry for the case of algebraic curves defined by means of polynomial parametrizations. The algorithms are based on the existence of a linear relationship between two…

Algebraic Geometry · Mathematics 2012-12-27 Juan G. Alcazar

We present a systematic methodology for the reformulation of a broad class of three-dimensional (3D) piezoelectric problems into a two-dimensional (2D) mathematical form. The sole underlying hypothesis is that the system geometry and…

Mesoscale and Nanoscale Physics · Physics 2016-08-31 H. T. Mengistu , A. García-Cristóbal

The integration of machine learning techniques in materials discovery has become prominent in materials science research and has been accompanied by an increasing trend towards open-source data and tools to propel the field. Despite the…

Materials Science · Physics 2026-05-27 Daniel Persaud , Logan Ward , Jason Hattrick-Simpers

We study the existence of polynomial kernels for the problem of deciding feasibility of integer linear programs (ILPs), and for finding good solutions for covering and packing ILPs. Our main results are as follows: First, we show that the…

Computational Complexity · Computer Science 2013-02-18 Stefan Kratsch

On the base of Lie algebraic and differential geometry methods, a wide class of multidimensional nonlinear integrable systems is obtained, and the integration scheme for such equations is proposed.

High Energy Physics - Theory · Physics 2008-02-03 A. V. Razumov , M. V. Saveliev

We consider a strongly heterogeneous medium saturated by an incompressible viscous fluid as it appears in geomechanical modeling. This poroelasticity problem suffers from rapidly oscillating material parameters, which calls for a thorough…

Numerical Analysis · Mathematics 2018-12-27 Robert Altmann , Eric Chung , Roland Maier , Daniel Peterseim , Sai-Mang Pun

This dissertation presents new results on three different themes all related to matroid polytopes. First we investigate properties of Ehrhart polynomials of matroid polytopes, independence matroid polytopes, and polymatroids. We prove that…

Combinatorics · Mathematics 2009-05-28 David C. Haws

Problems of flexible mechanical metamaterials, and highly deformable porous solids in general, are rich and complex due to nonlinear mechanics and nontrivial geometrical effects. While numeric approaches are successful, analytic tools and…

Soft Condensed Matter · Physics 2022-06-08 Yohai Bar-Sinai , Gabriele Librandi , Katia Bertoldi , Michael Moshe

Polynomial algebra offers a standard approach to handle several problems in geometric modeling. A key tool is the discriminant of a univariate polynomial, or of a well-constrained system of polynomial equations, which expresses the…

Algebraic Geometry · Mathematics 2013-04-23 Alicia Dickenstein , Ioannis Emiris , Anna Karasoulou

We develop a new tool, namely polynomial and linear algebraic methods, for studying systems of word equations. We illustrate its usefulness by giving essentially simpler proofs of several hard problems. At the same time we prove extensions…

Combinatorics · Mathematics 2015-02-10 Aleksi Saarela

One of basic difficulties of machine learning is handling unknown rotations of objects, for example in image recognition. A related problem is evaluation of similarity of shapes, for example of two chemical molecules, for which direct…

Machine Learning · Computer Science 2018-01-04 Jarek Duda

This paper proposes new algorithms for the metric learning problem. We start by noticing that several classical metric learning formulations from the literature can be viewed as modified covariance matrix estimation problems. Leveraging…

Machine Learning · Statistics 2022-11-23 Antoine Collas , Arnaud Breloy , Guillaume Ginolhac , Chengfang Ren , Jean-Philippe Ovarlez

We use radial basis functions to model the input--output response of an electronic device. A new methodology for producing models that accuratly describe the response of the device over a wide range of operating points is introduced. A key…

chao-dyn · Physics 2009-10-31 David M. Walker , R. Brown , N. B. Tufillaro

In this chapter, we identify fundamental geometric structures that underlie the problems of sampling, optimisation, inference and adaptive decision-making. Based on this identification, we derive algorithms that exploit these geometric…

We develop a geometric framework for the numerical integration of mechanical systems evolving on manifolds. After briefly reviewing classical numerical methods and highlighting their limitations and shortcomings in non-flat (non-Euclidean)…

General Mathematics · Mathematics 2026-03-30 Viyom Vivek , David Martin de Diego , Ravi N. Banavar

Nowadays, there are several complex systems in different sectors such as aviation, air traffic control ...etc. These systems do not have a precise perimeter, they are open and made of various specific components built with different…

Software Engineering · Computer Science 2025-05-28 Abdelkader Khouass , christian attiogbé , mohamed messabihi

We introduce an algorithm which can be directly used to feasible and optimum search in linear programming. Starting from an initial point the algorithm iteratively moves a point in a direction to resolve the violated constraints. At the…

Optimization and Control · Mathematics 2023-12-05 Denys Shcherbak , Natalya Pya Arnqvist

Calibration is commonly evaluated by comparing model confidence with its empirical correctness, implicitly treating reliability as a function of the confidence score alone. However, this view can hide substantial structure: models may be…

Machine Learning · Computer Science 2026-05-14 Katarzyna Kobalczyk , Mihaela van der Schaar