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Related papers: Geometric structures in pseudo-random graphs

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A general model for geometric structures on differentiable manifolds is obtained by deforming infinitesimal symmetries. Specifically, this model consists of a Lie algebroid, equipped with an affine connection compatible with the Lie…

Differential Geometry · Mathematics 2012-03-07 Anthony D. Blaom

In analogy with the spectral theory of geometrically finite hyperbolic manifolds, we initiate the study of resonances on geometrically finite (q+1)-regular graphs of groups. We prove the meromorphic continuation of the resolvent of the…

Spectral Theory · Mathematics 2026-03-30 Christian Arends , Carsten Peterson , Tobias Weich

Metric graphs are often introduced based on combinatorics, upon "associating" each edge of a graph with an interval; or else, casually "gluing" a collection of intervals at their endpoints in a network-like fashion. Here we propose an…

Combinatorics · Mathematics 2021-03-17 Delio Mugnolo

These lecture notes are a personal introduction to signed graphs, concentrating on the aspects that have been most persistently interesting to me. They are just a few corners of signed graph theory; I am leaving out a great deal. The…

Combinatorics · Mathematics 2016-10-18 Thomas Zaslavsky

Hierarchical structure and repetition are prevalent in graphs originating from nature or engineering. These patterns can be represented by a class of parametric-structure graphs, which are defined by templates that generate structure by way…

Data Structures and Algorithms · Computer Science 2020-11-16 Tal Ben-Nun , Lukas Gianinazzi , Torsten Hoefler , Yishai Oltchik

In this paper we introduce elements of algebraic geometry over an arbitrary algebraic structure. We prove Unification Theorems which gather the description of coordinate algebras by several ways.

Algebraic Geometry · Mathematics 2011-02-03 Evelina Daniyarova , Alexei Myasnikov , Vladimir Remeslennikov

A mixed graph can be seen as a type of digraph containing some edges (two opposite arcs). Here we introduce the concept of sequence mixed graphs, which is a generalization of both sequence graphs and iterated line digraphs. These structures…

Combinatorics · Mathematics 2016-10-13 C. Dalfó , M. A. Fiol , N. López

This is a brief review, in relatively non-technical terms, of recent advances in the theory of random field geometry. These advances have provided a collection of explicit new formulae describing mean values of a variety of geometric…

Probability · Mathematics 2008-05-08 Robert J Adler

We begin by defining general hypergeometric functions over finite fields and obtaining a finite field analogue of a classical symmetry in their complex counterparts. We give a geometric proof for the symmetry by constructing isomorphisms…

Number Theory · Mathematics 2026-04-22 Akio Nakagawa

We introduce the notion of geometric pseudo-quantisation based on geometric quantisation with a weakened curvature condition. We show how such a structure arises naturally from simple deformations of the symplectic structure and pullbacks…

Mathematical Physics · Physics 2025-11-25 Kerr Maxwell

We study counting limit laws that compare length functions on infinite graphs. We then apply these results to flat surfaces to obtain a statistical comparison between the geometric length and the number of singularities visited by geodesic…

Dynamical Systems · Mathematics 2025-03-18 Stephen Cantrell , Mark Pollicott

The concept of quasi-partial b-metric-like spaces is being introduced and studied with the help of topology. Examples are also discussed to support the results. Some fixed point theorems are proved in the setting of quasi-partial…

General Topology · Mathematics 2018-12-04 Anuradha Gupta , Manu Rohilla

Recovering hidden graph-like structures from potentially noisy data is a fundamental task in modern data analysis. Recently, a persistence-guided discrete Morse-based framework to extract a geometric graph from low-dimensional data has…

Computational Geometry · Computer Science 2018-03-22 Tamal K. Dey , Jiayuan Wang , Yusu Wang

We study the problem of detecting local geometry in random graphs. We introduce a model $\mathcal{G}(n, p, d, k)$, where a hidden community of average size $k$ has edges drawn as a random geometric graph on $\mathbb{S}^{d-1}$, while all…

Statistics Theory · Mathematics 2026-03-26 Jinho Bok , Shuangping Li , Sophie H. Yu

In this paper, we investigate the induced subgraphs of percolated random geometric graphs, and get some asymptotic results for the expected number of the subgraphs. Moreover, we get the Poisson approximation for the counting by Stein's…

Probability · Mathematics 2018-03-08 Anshui Li

We describe recent links between two topics: geometric structures on manifolds in the sense of Ehresmann and Thurston, and dynamics "at infinity" for representations of discrete groups into Lie groups.

Geometric Topology · Mathematics 2018-02-21 Fanny Kassel

Statistical graph models aim at modeling graphs as random realization among a set of possible graphs. One issue is to evaluate whether or not a graph is likely to have been generated by one particular model. In this paper we introduce the…

Social and Information Networks · Computer Science 2022-03-29 Louis Duvivier , Rémy Cazabet , Céline Robardet

We study the problem of detecting the presence of an underlying high-dimensional geometric structure in a random graph. Under the null hypothesis, the observed graph is a realization of an Erd\H{o}s-R\'enyi random graph $G(n,p)$. Under the…

Statistics Theory · Mathematics 2015-11-24 Sébastien Bubeck , Jian Ding , Ronen Eldan , Miklós Rácz

Based on methods of structural convergence we provide a unifying view of local-global convergence, fitting to model theory and analysis. The general approach outlined here provides a possibility to extend the theory of local-global…

Combinatorics · Mathematics 2018-10-18 Jaroslav Nesetril , Patrice Ossona de Mendez

We investigate the geometrical structure of probabilistic generative dimensionality reduction models using the tools of Riemannian geometry. We explicitly define a distribution over the natural metric given by the models. We provide the…

Machine Learning · Statistics 2014-12-01 Alessandra Tosi , Søren Hauberg , Alfredo Vellido , Neil D. Lawrence
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