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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

The extended persistence diagram is an invariant of piecewise linear functions, which is known to be stable under perturbations of functions with respect to the bottleneck distance as introduced by Cohen-Steiner, Edelsbrunner, and Harer. We…

Algebraic Topology · Mathematics 2024-07-08 Ulrich Bauer , Magnus Bakke Botnan , Benedikt Fluhr

In this paper, we consider topological featurizations of data defined over simplicial complexes, like images and labeled graphs, obtained by convolving this data with various filters before computing persistence. Viewing a convolution…

Algebraic Topology · Mathematics 2024-01-26 Elchanan Solomon , Paul Bendich

Dyson's short-distance universality of the correlation functions implies the universality of P(s), the level-spacing distribution. We first briefly review how this property is understood for unitary invariant ensembles and consider next a…

Mesoscale and Nanoscale Physics · Physics 2009-10-30 E. Brezin , S. Hikami

We study notions of hyperuniformity for invariant locally square-integrable point processes in regular trees. We show that such point processes are never geometrically hyperuniform, and if the diffraction measure has support in the…

Probability · Mathematics 2024-09-18 Mattias Byléhn

We prove the transversality result necessary for defining local Morse chain complexes with finite cyclic group symmetry. Our arguments use special regularized distance functions constructed using classical covering lemmas, and an inductive…

Symplectic Geometry · Mathematics 2018-09-18 Doris Hein , Umberto L. Hryniewicz , Leonardo Macarini

Persistent homology is a popular and powerful tool for capturing topological features of data. Advances in algorithms for computing persistent homology have reduced the computation time drastically -- as long as the algorithm does not…

Computational Geometry · Computer Science 2013-10-03 Ulrich Bauer , Michael Kerber , Jan Reininghaus

Consider a Poisson point process within a convex set in a Euclidean space. The Vietoris-Rips complex is the clique complex over the graph connecting all pairs of points with distance at most $\delta$. Summing powers of the volume of all…

Probability · Mathematics 2019-12-03 G. Akinwande , M. Reitzner

We develop novel methods for using persistent homology to infer the homology of an unknown Riemannian manifold $(M, g)$ from a point cloud sampled from an arbitrary smooth probability density function. Standard distance-based filtered…

Computational Geometry · Computer Science 2022-01-07 Abigail Hickok

The \v{C}ech and Rips constructions of persistent homology are stable with respect to perturbations of the input data. However, neither is robust to outliers, and both can be insensitive to topological structure of high-density regions of…

Algebraic Topology · Mathematics 2022-04-29 Andrew J. Blumberg , Michael Lesnick

Given a compact geodesic space $X$ we apply the fundamental group and alternatively the first homology group functor to the corresponding Rips or \v{C}ech filtration of $X$ to obtain what we call a persistence. This paper contains the…

Geometric Topology · Mathematics 2024-09-18 Žiga Virk

Persistent homology captures the appearances and disappearances of topological features such as loops and holes when growing disks centered at a Poisson point process. We study extreme values for the life times of features dying in bounded…

Probability · Mathematics 2020-09-29 Nicolas Chenavier , Christian Hirsch

We study the persistent homology of an Erd\H{o}s--R\'enyi random clique complex filtration on $n$ vertices. Here, each edge $e$ appears at a time $p_e \in [0,1]$ chosen uniform randomly in the interval, and the \emph{persistence} of a cycle…

Combinatorics · Mathematics 2022-09-14 Ayat Ababneh , Matthew Kahle

Recently, multi-scale notions of local homology (a variant of persistent homology) have been used to study the local structure of spaces around a given point from a point cloud sample. Current reconstruction guarantees rely on constructing…

Computational Geometry · Computer Science 2013-04-24 Primoz Skraba , Bei Wang

We introduce topological conditions on a broad class of functionals that ensure that the persistent homology modules of their associated sublevel set filtration admit persistence diagrams, which, in particular, implies that they satisfy…

Algebraic Topology · Mathematics 2024-01-08 Ulrich Bauer , Anibal M. Medina-Mardones , Maximilian Schmahl

We study random-matrix ensembles with a non-Gaussian probability distribution $P(H) \sim \exp (-N {\rm tr }\, V(H))$ where $N$ is the dimension of the matrix $H$ and $V(H)$ is independent of $N$. Using Efetov's supersymmetry formalism, we…

Condensed Matter · Physics 2009-10-22 G. Hackenbroich , H. A. Weidenmueller

Persistent homology naturally addresses the multi-scale topological characteristics of the large-scale structure as a distribution of clusters, loops, and voids. We apply this tool to the dark matter halo catalogs from the Quijote…

Cosmology and Nongalactic Astrophysics · Physics 2024-10-31 Jacky H. T. Yip , Matteo Biagetti , Alex Cole , Karthik Viswanathan , Gary Shiu

We prove two universality results for random tensors of arbitrary rank D. We first prove that a random tensor whose entries are N^D independent, identically distributed, complex random variables converges in distribution in the large N…

Probability · Mathematics 2013-05-07 Razvan Gurau

Nourdin et al. [9] established the following universality result: if a sequence of off-diagonal homogeneous polynomial forms in i.i.d. standard normal random variables converges in distribution to a normal, then the convergence also holds…

Probability · Mathematics 2015-05-15 Shuyang Bai , Murad S. Taqqu

Persistent (co)homology is a central construction in topological data analysis, where it is used to quantify prominence of features in data to produce stable descriptors suitable for downstream analysis. Persistence is challenging to…

Computational Geometry · Computer Science 2024-10-23 Arnur Nigmetov , Dmitriy Morozov