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Related papers: Attractor Networks on Complex Flag Manifolds

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In this paper two important aspects related to Caputo fractional-order discrete variant of a class of maps defined on the complex plane, are analytically and numerically revealed: attractors symmetry-broken induced by the fractional-order…

Dynamical Systems · Mathematics 2022-04-19 Marius-F. Danca

The paper considers systems of contraction similarities in $\mathbb R^d$ sending a given polyhedron $P$ to polyhedra $P_i\subset P$, whose non-empty intersections are singletons and contain the common vertices of those polyhedra, while the…

Metric Geometry · Mathematics 2017-07-11 Andrei Tetenov , Mary Samuel , Dmitry Vaulin

In the present work, we study the attractors of iterated function systems (IFSs) on connected and compact metric spaces. We prove that the whole of the phase space of a forward minimal IFS, for which some map admits an attracting fixed…

Dynamical Systems · Mathematics 2023-03-23 Aliasghar Sarizadeh

In this paper we obtain a detailed description of the global and cocycle attractors for the skew-product semiflows induced by the mild solutions of a family of scalar linear-dissipative parabolic problems over a minimal and uniquely ergodic…

Dynamical Systems · Mathematics 2017-12-15 Tomas Caraballo , Jose antonio Lnaga , Rafael Obaya , Ana M. Sanz

We study the attractor of Iterated Function Systems composed of infinitely many affine, homogeneous maps. In the special case of second generation IFS, defined herein, we conjecture that the attractor consists of a finite number of…

Dynamical Systems · Mathematics 2013-11-20 Giorgio Mantica

Inspired by Pansiot's work on substitutions, we prove a similar theorem for automorphisms of a free group F of finite rank: if a right-infinite word X represents an attracting fixed point of an automorphism of F, the subword complexity of X…

Group Theory · Mathematics 2025-06-04 Arnaud Hilion , Gilbert Levitt

Complex networks can be used to represent and model an ample diversity of abstract and real-world systems and structures. A good deal of the research on these structures has focused on specific topological properties, including node degree,…

Social and Information Networks · Computer Science 2023-11-08 Alexandre Benatti , Luciano da F. Costa

Complex network topology might get pretty complicated challenging many network analysis objectives, such as community detection for example. This however makes common emergent network phenomena such as scale-free topology or small-world…

Social and Information Networks · Computer Science 2018-06-12 Stanislav Sobolevsky

The article focuses on word (or string) attractors, which are sets of positions related to the text compression efficiency of the underlying word. The article presents two combinatorial algorithms based on Suffix automata or Directed…

Data Structures and Algorithms · Computer Science 2025-09-11 Marie-Pierre Béal , Maxime Crochemore , Giuseppe Romana

For a continuously differentiable Kolmogorov map defined from the nonnegative orthant to itself, a type-K competitive system is defined. Under the assumptions that the system is dissipative and the origin is a repeller, the global dynamics…

Dynamical Systems · Mathematics 2025-04-24 Zhanyuan Hou

Consideration of various hydrodynamic phenomena involves the study of the Navier-Stokes (N-S) equations, what is hard enough for analytical and numerical investigations since already in three-dimensional (3D) case it is a challenging task…

Chaotic Dynamics · Physics 2016-11-22 N. V. Kuznetsov , G. A. Leonov , T. N. Mokaev

This paper contains four main results associated with an attractor of a projective iterated function system (IFS). The first theorem characterizes when a projective IFS has an attractor which avoids a hyperplane. The second theorem…

Dynamical Systems · Mathematics 2015-03-13 Michael F. Barnsley , Andrew Vince

Computation of persistent homology of simplicial representations such as the Rips and the C\v{e}ch complexes do not efficiently scale to large point clouds. It is, therefore, meaningful to devise approximate representations and evaluate the…

Computational Geometry · Computer Science 2020-09-29 Naheed Anjum Arafat , Debabrota Basu , Stéphane Bressan

To simplify the analysis of Boolean networks, a reduction in the number of components is often considered. A popular reduction method consists in eliminating components that are not autoregulated, using variable substitution. In this work,…

Discrete Mathematics · Computer Science 2024-03-27 Robert Schwieger , Elisa Tonello

In this paper, we propose several consensus protocols of the first and second order for networked multi-agent systems and provide explicit representations for their asymptotic states. These representations involve the eigenprojection of the…

Optimization and Control · Mathematics 2018-11-27 Rafig Agaev , Pavel Chebotarev

Random Boolean networks, originally invented as models of genetic regulatory networks, are simple models for a broad class of complex systems that show rich dynamical structures. From a biological perspective, the most interesting networks…

Disordered Systems and Neural Networks · Physics 2009-11-07 Joshua E. S. Socolar , Stuart A. Kauffman

We show that graphs, networks and other related discrete model systems carry a natural supersymmetric structure, which, apart from its conceptual importance as to possible physical applications, allows to derive a series of spectral…

Mathematical Physics · Physics 2011-07-19 Manfred Requardt

We illuminate the relation between the Bruhat order on the symmetric group and structure constants (Littlewood-Richardson coefficients) for the cohomology of the flag manifold in terms of its basis of Schubert classes. Equivalently, the…

alg-geom · Mathematics 2016-11-08 Nantel Bergeron , Frank Sottile

Network Models with couplings between link pairs are the simplest models for a class of networks with Higher Order interactions. In this paper we give an analytic, general solution to this family of Random Graph Models extending previous…

Statistical Mechanics · Physics 2025-03-28 Alessio Catanzaro , Subodh Patil , Diego Garlaschelli

We study neural architectures in which each hidden layer is defined by the stationary state of a dissipative Schr\"odinger-type dynamics on a learned latent graph. On stable branches, the local stationary problem defines a differentiable…

Machine Learning · Computer Science 2026-04-28 Dmitry Pasechnyuk-Vilensky , Martin Takáč