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Jamming is a phenomenon shared by a wide variety of systems, such as granular materials, foams, and glasses in their high density regime. This has motivated the development of a theoretical framework capable of explaining many of their…

Statistical Mechanics · Physics 2021-06-24 Rafael Díaz Hernández Rojas , Giorgio Parisi , Federico Ricci-Tersenghi

Quasi-2D bidisperse amorphous systems of steel beads are fluidized by a uniform upflow of air, so that the beads roll on a horizontal plane. The short-time ballistic motion of the beads is stochastic, with non-Gaussian speed distributions…

Soft Condensed Matter · Physics 2007-05-23 A. R. Abate , D. J. Durian

Persistent homology computes the multiscale topology of a data set by using a sequence of discrete complexes. In this paper, we propose that persistent homology may be a useful tool for studying the structure of the landscape of string…

High Energy Physics - Theory · Physics 2019-04-24 Alex Cole , Gary Shiu

Topological data analysis provides a set of tools to uncover low-dimensional structure in noisy point clouds. Prominent amongst the tools is persistence homology, which summarizes birth-death times of homological features using data objects…

Methodology · Statistics 2024-02-05 James Matuk , Sebastian Kurtek , Karthik Bharath

As amorphous materials get jammed, both geometric and dynamic heterogeneity are observed. We investigate the correlation between the local geometric heterogeneity and local rearrangements in a slowly compressed bidisperse…

Soft Condensed Matter · Physics 2024-03-21 Xin Du , Eric R. Weeks

Persistent homology analysis provides means to capture the connectivity structure of data sets in various dimensions. On the mathematical level, by defining a metric between the objects that persistence attaches to data sets, we can…

Machine Learning · Computer Science 2019-06-12 Henri Riihimäki , José Licón-Saláiz

Hyperuniformity, the suppression of density fluctuations at large length scales, is observed across a wide variety of domains, from cosmology to condensed matter and biological systems. Although the standard definition of hyperuniformity…

Statistical Mechanics · Physics 2024-05-07 Marco Salvalaglio , Dominic J. Skinner , Jörn Dunkel , Axel Voigt

We prove the emergence of spatially correlated dynamics in slowly compacting dense granular media by analyzing analytically and numerically multi-point correlation functions in a simple particle model characterized by slow non-equilibrium…

Statistical Mechanics · Physics 2009-11-10 Alexandre Lefèvre , Ludovic Berthier , Robin Stinchcombe

Interest in the dynamical arrest leading to a fluid --> solid transition in thermal and athermal systems has led to questions about the nature of these transitions. These jamming transitions may be dependent on the influence of extended…

Soft Condensed Matter · Physics 2007-05-23 Allison Ferguson , Bulbul Chakraborty

Spatial transcriptomics studies are becoming increasingly large and commonplace, necessitating simultaneous analysis of a large number of spatially resolved variables. Correspondingly, a diverse range of methodologies have been proposed to…

Quantitative Methods · Quantitative Biology 2025-09-09 James Boyle , Gregory Hamm , Eleanor Williams , Robin JG Hartman , Magnus Soderburg , Ian Henry , Michael Casey

We track the motion of a horizontally vibrated amorphous assembly of bidisperse hard disks, for densities ranging across the jamming transition. We derive on very general grounds a bound on the dynamical susceptibility in terms of the…

Soft Condensed Matter · Physics 2008-08-26 F. Lechenault , O. Dauchot , G. Biroli , J. P. Bouchaud

We study the onset of spatial instabilities in reaction networks where the spatially homogeneous system admits a steady state parameterization. We formulate a sufficient condition -- based on the signs of the constant and leading…

Dynamical Systems · Mathematics 2026-05-18 Carsten Conradi , Maya Mincheva , Hannes Uecker

Phenomenological (P-type) bifurcations are qualitative changes in stochastic dynamical systems whereby the stationary probability density function (PDF) changes its topology. The current state of the art for detecting these bifurcations…

Algebraic Topology · Mathematics 2024-06-10 Sunia Tanweer , Firas A. Khasawneh

We develop in this paper a theoretical framework for the topological study of time series data. Broadly speaking, we describe geometrical and topological properties of sliding window (or time-delay) embeddings, as seen through the lens of…

Algebraic Topology · Mathematics 2013-11-26 Jose Perea , John Harer

Persistent homology is a topological data analysis tool that has been widely generalized, extending its scope beyond the field of topology. Among its extensions, steady and ranging persistence were developed to study a wide variety of graph…

Algebraic Topology · Mathematics 2026-05-15 Yann-Situ Gazull

We apply modern methods in computational topology to the task of discovering and characterizing phase transitions. As illustrations, we apply our method to four two-dimensional lattice spin models: the Ising, square ice, XY, and…

Statistical Mechanics · Physics 2021-10-04 Alex Cole , Gregory J. Loges , Gary Shiu

Understanding the physics of supercooled liquids near glassy transition remains one of the major challenges in condensed matter science. There has been long recognized that supercooled liquids have spatially dynamical heterogeneity whose…

Statistical Mechanics · Physics 2023-07-10 Viet Nguyen , Xueyu Song

Topological data analysis is an emerging area in exploratory data analysis and data mining. Its main tool, persistent homology, has become a popular technique to study the structure of complex, high-dimensional data. In this paper, we…

Graphics · Computer Science 2017-10-04 Mustafa Hajij , Bei Wang , Carlos Scheidegger , Paul Rosen

Persistent homology is a method for probing topological properties of point clouds and functions. The method involves tracking the birth and death of topological features (2000) as one varies a tuning parameter. Features with short…

In topological data analysis, we want to discern topological and geometric structure of data, and to understand whether or not certain features of data are significant as opposed to simply random noise. While progress has been made on…

Computational Geometry · Computer Science 2020-01-10 So Mang Han , Taylor Okonek , Nikesh Yadav , Xiaojun Zheng
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