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We propose a framework for descriptively analyzing sets of partial orders based on the concept of depth functions. Despite intensive studies in linear and metric spaces, there is very little discussion on depth functions for non-standard…

Machine Learning · Computer Science 2024-02-22 Hannah Blocher , Georg Schollmeyer , Malte Nalenz , Christoph Jansen

We develop a general formalism for representing and understanding structure in complex systems. In our view, structure is the totality of relationships among a system's components, and these relationships can be quantified using information…

Statistical Mechanics · Physics 2014-09-17 Benjamin Allen , Blake C. Stacey , Yaneer Bar-Yam

Dimensions of level sets of generic continuous functions and generic H\"older functions defined on a fractal $F$ encode information about the geometry, ``the thickness" of $F$. While in the continuous case this quantity is related to a…

Classical Analysis and ODEs · Mathematics 2024-10-10 Zoltán Buczolich , Balázs Maga , Gáspár Vértesy

Entropy is one of physical bases for fractal dimension definition, and the generalized fractal dimension was defined by Renyi entropy. Using fractal dimension, we can describe urban growth and form and characterize spatial complexity. A…

Physics and Society · Physics 2020-11-17 Yanguang Chen

This work was intended to be all about, and only about, hypergeometric 3F2(1). The initial goal was to revisit many identities from the literature that have been derived over the years and show that they can be obtained in a simpler way…

Classical Analysis and ODEs · Mathematics 2026-01-09 Michael Milgram

In this report we present experimental results using \emph{Haussdorf-Besicovich} fractal dimension for performing morphological galaxy classification. The fractal dimension is a topological, structural and spatial property that give us…

Computer Vision and Pattern Recognition · Computer Science 2017-06-26 Jorge de la Calleja , Elsa M. de la Calleja , Hugo Jair Escalante

The problem of defining and studying complexity of a time series has interested people for years. In the context of dynamical systems, Grassberger has suggested that a slow approach of the entropy to its extensive asymptotic limit is a sign…

Data Analysis, Statistics and Probability · Physics 2009-11-07 William Bialek , Ilya Nemenman , Naftali Tishby

In the past three decades, many theoretical measures of complexity have been proposed to help understand complex systems. In this work, for the first time, we place these measures on a level playing field, to explore the qualitative…

Information Theory · Computer Science 2017-08-01 Maxinder S. Kanwal , Joshua A. Grochow , Nihat Ay

Topological Data Analysis (TDA) uses insights from topology to create representations of data able to capture global and local geometric and topological properties. Its methods have successfully been used to develop estimations of fractal…

Physics concepts have often been borrowed and independently developed by other fields of science. In this perspective a significant example is that of entropy in Information Theory. The aim of this paper is to provide a short and…

Physics Education · Physics 2007-05-23 Andrea Baronchelli , Emanuele Caglioti , Vittorio Loreto

Multilayer networks preserve full information about the different interactions among the constituents of a complex system, and have recently proven quite useful in modelling transportation networks, social circles, and the human brain. A…

Physics and Society · Physics 2020-06-29 Andrea Santoro , Vincenzo Nicosia

Retrieval-Augmented Generation (RAG) systems are increasingly deployed on large-scale document collections, often comprising millions of documents and tens of millions of text chunks. In industrial-scale retrieval platforms, scalability is…

Information Retrieval · Computer Science 2026-01-08 Dario Maio , Stefano Rizzi

By viewing the covers of a fractal as a statistical mechanical system, the exact capacity of a multifractal is computed. The procedure can be extended to any multifractal described by a scaling function to show why the capacity and…

chao-dyn · Physics 2009-10-22 Ronnie Mainieri

The manifold of empirical mean values of statistical data ad infinitum has a geometric shape that depends on the probability measure that governs the generating model. Large deviation theory produces entropy functions that depend on both…

Information Theory · Computer Science 2026-05-07 Viswa Virinchi Muppirala , Hong Qian

Mean Hausdorff dimension is a dynamical version of Hausdorff dimension. It provides a way to dynamicalize geometric measure theory. We pick up the following three classical results of fractal geometry. (1) The calculation of Hausdorff…

Dynamical Systems · Mathematics 2022-09-02 Masaki Tsukamoto

The problem of evaluating the information associated with Fredholm integral equations of the first kind, when the integral operator is self-adjoint and compact, is considered here. The data function is assumed to be perturbed gently by an…

Classical Analysis and ODEs · Mathematics 2007-07-16 Enrico De Micheli , Giovanni Alberto Viano

We provide geometrical interpretation of the Master Theorem to solve divide-and-conquer recurrences. We show how different cases of the recurrences correspond to different kinds of fractal images. Fractal dimension and Hausdorff measure are…

Data Structures and Algorithms · Computer Science 2016-09-08 Simant Dube

We present an information-theoretic analysis of the Cosmic Web that goes beyond the scalar density contrast and exploits the full structure of the tidal deformation tensor. The three eigenvalues ($\lambda_1, \lambda_2, \lambda_3$) of the…

Cosmology and Nongalactic Astrophysics · Physics 2026-05-26 Juan Garcia-Bellido

One approach to confronting computational hardness is to try to understand the contribution of various parameters to the running time of algorithms and the complexity of computational tasks. Almost no computational tasks in real life are…

Computational Complexity · Computer Science 2011-11-23 Rodney G. Downey , Dimitrios M. Thilikos

The input data features set for many data driven tasks is high-dimensional while the intrinsic dimension of the data is low. Data analysis methods aim to uncover the underlying low dimensional structure imposed by the low dimensional hidden…

Machine Learning · Computer Science 2019-01-30 Moshe Salhov , Ofir Lindenbaum , Yariv Aizenbud , Avi Silberschatz , Yoel Shkolnisky , Amir Averbuch