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The optimal wavelet basis is used to develop quantitative, experimentally applicable criteria for self-organization. The choice of the optimal wavelet is based on the model of self-organization in the wavelet tree. The framework of the…

Mathematical Physics · Physics 2015-06-05 Milos Milovanovic , Milan Rajkovic

We describe a simple automated method to extract and quantify transient heterogeneous dynamical changes from large datasets generated in single molecule/particle tracking experiments. Based on wavelet transform, the method transforms raw…

Data Analysis, Statistics and Probability · Physics 2013-06-04 Kejia Chen , Bo Wang , Juan Guan , Steve Granick

Biological processes involve a variety of spatial and temporal scales. A holistic understanding of many biological processes therefore requires multi-scale models which capture the relevant properties on all these scales. In this manuscript…

Molecular Networks · Quantitative Biology 2015-06-23 Jan Hasenauer , Nick Jagiella , Sabrina Hross , Fabian J. Theis

Long-lived flow patterns in the atmosphere such as weather fronts, mid-latitude blockings or tropical cyclones often induce extreme weather conditions. As a consequence, their description, detection, and tracking has received increasing…

Networks have in recent years emerged as an invaluable tool for describing and quantifying complex systems in many branches of science. Recent studies suggest that networks often exhibit hierarchical organization, where vertices divide into…

Machine Learning · Statistics 2008-11-05 Aaron Clauset , Cristopher Moore , M. E. J. Newman

Inspired by topological data analysis techniques, we introduce persistent homology observables and apply them in a geometric analysis of the dynamics of quantum field theories. As a prototype application, we consider data from a…

Quantum Gases · Physics 2021-09-23 Daniel Spitz , Jürgen Berges , Markus K. Oberthaler , Anna Wienhard

Physical imaging is a foundational characterization method in areas from condensed matter physics and chemistry to astronomy and spans length scales from atomic to universe. Images encapsulate crucial data regarding atomic bonding,…

An ultrametric topology formalizes the notion of hierarchical structure. An ultrametric embedding, referred to here as ultrametricity, is implied by a hierarchical embedding. Such hierarchical structure can be global in the data set, or…

Methodology · Statistics 2011-01-11 Fionn Murtagh

This article discusses the description of wall-bounded turbulence as a deterministic high-dimensional dynamical system of interacting coherent structures, defined as eddies with enough internal dynamics to behave relatively autonomously…

Fluid Dynamics · Physics 2018-03-20 Javier Jimenez

Turbulence is a complex system exhibiting both universal statistical features and prominent coherent structures. We model turbulence using coherent vortices distributed within a multi-scale statistical framework, termed `woven turbulence'.…

Fluid Dynamics · Physics 2025-12-04 Zishuo Han , Weiyu Shen , Yue Yang

The dynamics of small-scale structures in free-surface turbulence is crucial to large-scale phenomena in natural and industrial environments. Here we conduct experiments on the quasi-flat free surface of a zero-mean-flow turbulent water…

Fluid Dynamics · Physics 2025-03-14 Yinghe Qi , Yaxing Li , Filippo Coletti

This article reviews recent developments in multiresolution analysis which make it a powerful tool for the systematic treatment of the multiple length-scales inherent in the electronic structure of matter. Although the article focuses on…

Materials Science · Physics 2009-10-31 T. A. Arias

An ultrametric topology formalizes the notion of hierarchical structure. An ultrametric embedding, referred to here as ultrametricity, is implied by a natural hierarchical embedding. Such hierarchical structure can be global in the data…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Fionn Murtagh

To comprehend the multipartite organization of large-scale biological and social systems, we introduce a new information theoretic approach that reveals community structure in weighted and directed networks. The method decomposes a network…

Physics and Society · Physics 2008-02-13 M. Rosvall , C. T. Bergstrom

In this paper we give a general account of Wave Interaction Theory which by now consists of two parts: kinetic wave turbulence theory (WTT), using a statistical description of wave interactions, and the D-model recently introduced in…

Fluid Dynamics · Physics 2013-10-22 Elena Kartashova

Turbulent flows present rich dynamics originating from non-trivial energy fluxes across scales, non-stationary forcings and geometrical constraints. This complexity manifests in non-hyperbolic chaos, randomness, state-dependent persistence…

Data-driven methods play an increasingly important role in discovering geometric, structural, and semantic relationships between 3D shapes in collections, and applying this analysis to support intelligent modeling, editing, and…

Graphics · Computer Science 2015-02-25 Kai Xu , Vladimir G. Kim , Qixing Huang , Evangelos Kalogerakis

In recent years there has been noticeable interest in the study of the "shape of data". Among the many ways a "shape" could be defined, topology is the most general one, as it describes an object in terms of its connectivity structure:…

Machine Learning · Statistics 2017-09-22 Tullia Padellini , Pierpaolo Brutti

Many questions remain in turbulence research---and related fields---about the underlying physical processes that transfer scalar quantities, such as the kinetic energy, between different length scales. Measurement of an ensemble-averaged…

Soft Condensed Matter · Physics 2007-05-23 M. K. Rivera , W. B. Daniel , S. Y. Chen , R. E. Ecke

In this paper, I outline several conceptual and methodological issues related to modeling individual and group processes embedded in clustered/hierarchical data structures. We position multilevel modeling techniques within a broader set of…

Methodology · Statistics 2022-12-29 Amira Ibrahim El-Desokey
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