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Related papers: Scale-local dimensions of strange attractors

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The local dimension spectrum provides a framework for quantifying the fractal properties of a measure, and it is well understood for non-overlapping self-similar measures. In this article, we study the local dimension spectrum for dominated…

Dynamical Systems · Mathematics 2026-01-21 Alex Batsis , Antti Käenmäki , Tom Kempton

This work will appear as a chapter in a forthcoming volume titled "Topics in Probabilistic Graph Theory". A theory of scaling limits for random graphs has been developed in recent years. This theory gives access to the large-scale geometric…

Probability · Mathematics 2024-10-18 Louigi Addario-Berry , Christina Goldschmidt

Dimension is a fundamental property of objects and the space in which they are embedded. Yet ideal notions of dimension, as in Euclidean spaces, do not always translate to physical spaces, which can be constrained by boundaries and…

Physics and Society · Physics 2022-07-06 Robert L. Peach , Alexis Arnaudon , Mauricio Barahona

We consider random rectangles in $\mathbb{R}^2$ that are distributed according to a Poisson random measure, i.e., independently and uniformly scattered in the plane. The distributions of the length and the width of the rectangles are…

Probability · Mathematics 2018-06-29 Frank Aurzada , Sebastian Schwinn

We seek a practical method for establishing dense correspondences between two images with similar content, but possibly different 3D scenes. One of the challenges in designing such a system is the local scale differences of objects…

Computer Vision and Pattern Recognition · Computer Science 2016-04-20 Moria Tau , Tal Hassner

Let $G$ be a graph and $S\subseteq V(G)$. If every two adjacent vertices of $G$ have different metric $S$-representations, then $S$ is a local metric generator for $G$. A local metric generator of smallest order is a local metric basis for…

Combinatorics · Mathematics 2019-02-26 Sandi Klavžar , Mostafa Tavakoli

An important problem in the analysis of experimental data showing fractal properties, is that such samples are composed by a set of points limited by an upper and a lower cut off. We study how finite size effect due to the discreteness of…

Condensed Matter · Physics 2007-05-23 A. Amici , M. Montuori

The dimension of random simplicial complexes (defined as the maximal dimension among all faces) is a natural extreme value associated with the complex, and is closely related to other functionals defined by a maximum, such as the clique…

Probability · Mathematics 2025-12-19 Kinga Nagy

We define several new models for how to define anomalous regions among enormous sets of trajectories. These are based on spatial scan statistics, and identify a geometric region which captures a subset of trajectories which are…

Data Structures and Algorithms · Computer Science 2019-06-06 Michael Matheny , Dong Xie , Jeff M. Phillips

A statistical measure of dimension is used to compute the effective average space dimension for the Internet and other graphs, based on typed edges (links) from an ensemble of starting points. The method is applied to CAIDA's ITDK data for…

Social and Information Networks · Computer Science 2022-03-15 Mark Burgess

We present a simple yet rigorous approach to the determination of the spectral dimension of random trees, based on the study of the massless limit of the Gaussian model on such trees. As a byproduct, we obtain evidence in favor of a new…

Condensed Matter · Physics 2008-11-26 C. Destri , L. Donetti

We consider the dimensions of finite type of representations of a partially ordered set, i.e. such that there is only finitely many isomorphism classes of representations of this dimension. We give a criterion for a dimension to be of…

Representation Theory · Mathematics 2012-01-24 Yuriy A. Drozd , Eugene A. Kubichka

We introduce and analyze a class of growing geometric random graphs that are invariant under rescaling of space and time. Directed connections between nodes are drawn according to influence zones that depend on node position in space and…

Physics and Society · Physics 2016-03-23 Zheng Xie , Tim Rogers

The intrinsic dimensionality refers to the ``true'' dimensionality of the data, as opposed to the dimensionality of the data representation. For example, when attributes are highly correlated, the intrinsic dimensionality can be much lower…

Machine Learning · Statistics 2020-11-30 Erik Thordsen , Erich Schubert

We study the geometric and topological properties of strange non-chaotic attractors created in non-smooth saddle-node bifurcations of quasiperiodically forced interval maps. By interpreting the attractors as limit objects of the iterates of…

Dynamical Systems · Mathematics 2014-12-22 Gabriel Fuhrmann , Maik Gröger , Tobias Jäger

In various disordered systems or non-equilibrium dynamical models, the large deviations of some observables have been found to display different scalings for rare values bigger or smaller than the typical value. In the present paper, we…

Statistical Mechanics · Physics 2021-05-12 Cecile Monthus

In this article we introduce associative Look-Up Tables. With their help, pseudo sums are correctly determined. The set of limit distributions in a pseudo-summation scheme of i.i.d. random variables is described. Also, two special cases…

Probability · Mathematics 2023-06-02 Ivan Alexeev , Ignat Melnikov , Artem Uglovski

We argue that dimensionality is not absolute, but that it depends on the scale of resolution, from the Planck to the macro scale.

General Physics · Physics 2015-06-26 B. G. Sidharth

Scaling laws are powerful summaries of the variations of urban attributes with city size. However, the validity of their universal meaning for cities is hampered by the observation that different scaling regimes can be encountered for the…

Physics and Society · Physics 2016-06-15 Clementine Cottineau , Erez Hatna , Elsa Arcaute , Michael Batty

We show that a knowledge of diagonal partons at a low scale is sufficient to determine the off-diagonal (or skewed) distributions at a higher scale, to a good degree of accuracy. We quantify this observation by presenting results for the…

High Energy Physics - Phenomenology · Physics 2008-11-26 K. J. Golec-Biernat , A. D. Martin , M. G. Ryskin
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