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Related papers: From graphs to tensegrity structures: Geometric an…

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Consider a graph G with n vertices. In this paper we study geometric conditions for an n-tuple of points in R^d to admit a tensegrity with underlying graph G. We introduce and investigate a natural stratification, depending on G, of the…

Combinatorics · Mathematics 2008-07-01 Franck Doray , Oleg Karpenkov , Jan Schepers

In this paper we formulate and prove necessary and sufficient geometric conditions for existence of generic tensegrities in the plane for arbitrary graphs. The conditions are written in terms of "meet-join" relations for the configuration…

Metric Geometry · Mathematics 2015-12-09 O. Karpenkov

A classical tensegrity model consists of an embedded graph in a vector space with rigid bars representing edges, and an assignment of a stress to every edge such that at every vertex of the graph the stresses sum up to zero. The tensegrity…

Algebraic Geometry · Mathematics 2023-01-02 Fatemeh Mohammadi , Xian Wu

This paper proposes a unified approach for dynamic modeling and simulations of general tensegrity structures with rigid bars and rigid bodies of arbitrary shapes. The natural coordinates are adopted as a non-minimal description in terms of…

Computational Engineering, Finance, and Science · Computer Science 2024-08-30 Jiahui Luo , Xiaoming Xu , Zhigang Wu , Shunan Wu

Geometric modeling by constraints, whose applications are of interest to communities from various fields such as mechanical engineering, computer aided design, symbolic computation or molecular chemistry, is now integrated into standard…

Computational Geometry · Computer Science 2018-03-06 Samy Ait-Aoudia , Adel Moussaoui , Khaled Abid , Dominique Michelucci

Tensegrity structures have been extensively studied over the last years due to their potential applications in modern engineering like metamaterials, deployable structures, planetary lander modules, etc. Many of the form-finding methods…

Dynamical Systems · Mathematics 2024-02-14 Ajay B. Harish , Vijay Nandurdikar , Shubham Deshpande , Stephanie Andress

For any metric $d$ on $\mathbb{R}^2$, an ($\mathbb{R}^2,d$)-geometric graph is a graph whose vertices are points in $\mathbb{R}^2$, and two vertices are adjacent if and only if their distance is at most 1. If $d=\|.\|_{\infty}$, the metric…

Combinatorics · Mathematics 2016-10-26 Huda Chuangpishit , Jeannette Janssen

A $d$-dimensional tensegrity framework $(T,p)$ is an edge-labeled geometric graph in ${\mathbb R}^d$, which consists of a graph $T=(V,B\cup C\cup S)$ and a map $p:V\to {\mathbb R}^d$. The labels determine whether an edge $uv$ of $T$…

Combinatorics · Mathematics 2024-10-11 Adam D. W. Clay , Tibor Jordán , Sára Hanna Tóth

The persistence diagram (PD) is an increasingly popular topological descriptor. By encoding the size and prominence of topological features at varying scales, the PD provides important geometric and topological information about a space.…

We propose a universal approach to a range of enumeration problems in graphs. The key point is in contracting suitably chosen symmetric tensors placed at the vertices of a graph along the edges. In particular, this leads to an algorithm…

Combinatorics · Mathematics 2007-05-23 Peter Zograf

In this paper, we discuss tensegrity from the perspective of nonlinear algebra in a manner accessible to undergraduates. We compute explicit examples and include the SAGE and Julia code so that readers can continue their own experiments and…

Metric Geometry · Mathematics 2020-03-31 Alexander Heaton

We consider the problem of tensor completion with graphs serving as side information to represent interrelationships among variables. Existing approaches suffer from several limitations: (1) they are often task-specific and lack generality…

Machine Learning · Computer Science 2026-03-17 Kaidong Wang , Qianxin Yi , Yao Wang , Xiuwu Liao , Shaojie Tang , Can Yang

Graph convexity has been used as an important tool to better understand the structure of classes of graphs. Many studies are devoted to determine if a graph equipped with a convexity is a {\em convex geometry}. In this work we survey…

Discrete Mathematics · Computer Science 2024-09-05 Mitre C. Dourado , Marisa Gutierrez , Fábio Protti , Rudini Sampaio , Silvia Tondato

The content of this paper can be roughly organized into a three-level hierarchy of generality. At the first, most general level, we introduce a new language which allows us to express various categorical structures in a systematic and…

Mathematical Physics · Physics 2022-08-03 Andreas Bauer , Alexander Nietner

In this paper, we develop a novel paradigm, namely hypergraph shift, to find robust graph modes by probabilistic voting strategy, which are semantically sound besides the self-cohesiveness requirement in forming graph modes. Unlike the…

Artificial Intelligence · Computer Science 2017-04-13 Yang Wang , Lin Wu

In this paper we discuss several results about the structure of the configuration space of two-dimensional tensegrities with a small number of points. We briefly describe the technique of surgeries that is used to find geometric conditions…

Combinatorics · Mathematics 2012-01-18 Oleg Karpenkov , Jan Schepers , Brigitte Servatius

An important problem in geometric reasoning is to find the configuration of a collection of geometric bodies so as to satisfy a set of given constraints. Recently, it has been suggested that this problem can be solved efficiently by…

Artificial Intelligence · Computer Science 2009-09-25 S. Bhansali , G. A. Kramer , T. J. Hoar

This thesis studies the graph alignment problem, the noisy version of the graph isomorphism problem, which aims to find a matching between the nodes of two graphs which preserves most of the edges. Focusing on the planted version where the…

Data Structures and Algorithms · Computer Science 2024-04-22 Luca Ganassali

Geometric graphs are a special kind of graph with geometric features, which are vital to model many scientific problems. Unlike generic graphs, geometric graphs often exhibit physical symmetries of translations, rotations, and reflections,…

In recent years, Deep Learning methods have achieved state of the art performance in a vast range of machine learning tasks, including image classification and multilingual automatic text translation. These architectures are trained to…

Machine Learning · Computer Science 2020-12-15 Carlos Lassance
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