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The purpose of this article is to study Lipschitz CR mappings from an $h$-extendible (or semi-regular) hypersurface in $\mbb C^n$. Under various assumptions on the target hypersurface, it is shown that such mappings must be smooth. A…

Complex Variables · Mathematics 2011-02-15 G. P. Balakumar , Kaushal Verma

A generalization of the random geometric graph (RGG) model is proposed by considering a set of points uniformly and independently distributed on a rectangle of unit area instead of on a unit square [0,1]^2. The topological properties of the…

Physics and Society · Physics 2015-05-20 Ernesto Estrada , Matthew Sheerin

In this paper, we deal with the problem of reconstruction from Radon random samples in local shift-invariant signal space. Different from sampling after Radon transform, we consider sampling before Radon transform, where the sample set is…

Optimization and Control · Mathematics 2025-11-05 Zhanpeng Deng , Jiao Li , Jun Xian

We present a renormalization group (RG) procedure which works naturally on a wide class of interacting one-dimension models based on perturbed (possibly strongly) continuum conformal and integrable models. This procedure integrates Kenneth…

Strongly Correlated Electrons · Physics 2016-07-05 Robert M. Konik , Yury Adamov

We present a new approach to the problem of proving global stability, based on symplectic geometry and with a focus on systems with several conserved quantities. We also provide a proof of instability for integrable systems whose momentum…

Mathematical Physics · Physics 2025-10-28 Verónica Errasti Díez , Jordi Gaset Rifà , Manuel Lainz

The emergence of a variety of graph-based meaning representations (MRs) has sparked an important conversation about how to adequately represent semantic structure. These MRs exhibit structural differences that reflect different theoretical…

Computation and Language · Computer Science 2020-05-01 Lucia Donatelli , Jonas Groschwitz , Alexander Koller , Matthias Lindemann , Pia Weißenhorn

Renormalization group (RG) methods used to soften Hamiltonians allow large-scale computational resources to be used to greater advantage in calculations of nuclear structure and reactions. These RG transformations lower the effective…

Nuclear Theory · Physics 2013-09-24 R. J. Furnstahl

The renormalization group (RG) constitutes a fundamental framework in modern theoretical physics. It allows the study of many systems showing states with large-scale correlations and their classification in a relatively small set of…

Statistical Mechanics · Physics 2024-09-04 Guido Caldarelli , Andrea Gabrielli , Tommaso Gili , Pablo Villegas

Global resonance is a mechanism by which a homoclinic tangency of a smooth map can have infinitely many asymptotically stable, single-round periodic solutions. To understand the bifurcation structure one would expect to see near such a…

Dynamical Systems · Mathematics 2021-08-18 Sishu Shankar Muni , Robert I. McLachlan , David J. W. Simpson

We define 2-calibrated structures, which are analogs of symplectic structures in odd dimensions. We show the existence of differential topological constructions compatible with the structure.

Differential Geometry · Mathematics 2018-07-31 David Martinez Torres

A metric graph is a 1-dimensional stratified metric space consisting of vertices and edges or loops glued together. Metric graphs can be naturally used to represent and model data that take the form of noisy filamentary structures, such as…

Statistics Theory · Mathematics 2014-02-10 Fabrizio Lecci , Alessandro Rinaldo , Larry Wasserman

The spectral density of random graphs with topological constraints is analysed using the replica method. We consider graph ensembles featuring generalised degree-degree correlations, as well as those with a community structure. In each case…

Disordered Systems and Neural Networks · Physics 2011-04-08 Tim Rogers , Conrad Pérez Vicente , Koujin Takeda , Isaac Pérez Castillo

Persistent Homology (PH) and Artificial Neural Networks (ANNs) offer contrasting approaches to inferring topological structure from data. In this study, we examine the noise robustness of a supervised neural network trained to predict Betti…

Computer Vision and Pattern Recognition · Computer Science 2025-09-12 Dylan Peek , Matthew P. Skerritt , Stephan Chalup

Using particle-scale models to accurately describe property enhancements and phase transitions in macroscopic behavior is a major engineering challenge in composite materials science. To address some of these challenges, we use the graph…

Disordered Systems and Neural Networks · Physics 2018-09-12 Samuel Heroy , Dane Taylor , Feng Shi , M. Gregory Forest , Peter J. Mucha

We present numerical renormalization group (NRG) calculations for a single-impurity Anderson model with a linear coupling to a local phonon mode. We calculate dynamical response functions, spectral densities, dynamic charge and spin…

Strongly Correlated Electrons · Physics 2009-11-07 A. Hewson , D. Meyer

We investigate the Laplacian spectra of random geometric graphs (RGGs). The spectra are found to consist of both a discrete and a continuous part. The discrete part is a collection of Dirac delta peaks at integer values roughly centered…

Statistical Mechanics · Physics 2014-12-03 Amy Nyberg , Thilo Gross , Kevin E. Bassler

A topological condition is given, characterizing which closed manifolds in dimensions < 8 (and conjecturally in general) admit symplectic structures. The condition is the existence of a certain fibration-like structure called a hyperpencil.…

Symplectic Geometry · Mathematics 2007-05-23 Robert E. Gompf

Exploring and understanding topological phases in systems with strong distributed disorder requires developing fundamentally new approaches to replace traditional tools such as topological band theory. Here, we present a general real-space…

Disordered Systems and Neural Networks · Physics 2024-04-25 Zhe Zhang , Yifei Guan , Junda Wang , Benjamin Apffel , Aleksi Bossart , Haoye Qin , Oleg V. Yazyev , Romain Fleury

We use the persistent homology method of topological data analysis and dimensional analysis techniques to study data of syntactic structures of world languages. We analyze relations between syntactic parameters in terms of dimensionality,…

Computation and Language · Computer Science 2019-03-14 Alexander Port , Taelin Karidi , Matilde Marcolli

We show that resonance zones near an elliptic periodic point of a reversible map must, generically, contain asymptotically stable and asymptotically unstable periodic orbits, along with wild hyperbolic sets.

Dynamical Systems · Mathematics 2012-12-11 Sergey Gonchenko , Jeroen Lamb , Isabel Rios , Dmitry Turaev
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