English
Related papers

Related papers: Breaking of ensemble equivalence for dense random …

200 papers

In this paper, matching pairs of random graphs under the community structure model is considered. The problem emerges naturally in various applications such as privacy, image processing and DNA sequencing. A pair of randomly generated…

Cryptography and Security · Computer Science 2018-11-01 F. Shirani , S. Garg , E. Erkip

We analyze maximum entropy random graph ensembles with constrained degrees, drawn from arbitrary degree distributions, and a tuneable number of 3-loops (triangles). We find that such ensembles generally exhibit two transitions, a clustering…

Disordered Systems and Neural Networks · Physics 2020-08-26 Fabian Aguirre Lopez , Anthony CC Coolen

In this paper, we relate the problem of finding a maximum clique to the intersection number of the input graph (i.e. the minimum number of cliques needed to edge cover the graph). In particular, we consider the maximum clique problem for…

Discrete Mathematics · Computer Science 2012-04-19 S. Nikoletseas , C. Raptopoulos , P. G. Spirakis

Let $\mathbb{G}^{D}$ be the set of graphs $G(V,\, E)$ with $\left|V\right|=n$, and the degree sequence equal to $D=(d_{1},\, d_{2},\,\dots,\, d_{n})$. In addition, for $\frac{1}{2}<a<1$, we define the set of graphs with an almost given…

Probability · Mathematics 2014-02-24 Behzad Mehrdad

We show that sharp thresholds for Boolean functions directly imply average-case circuit lower bounds. More formally we show that any Boolean function exhibiting a sharp enough threshold at \emph{arbitrary} critical density cannot be…

Computational Complexity · Computer Science 2024-07-17 David Gamarnik , Elchanan Mossel , Ilias Zadik

The main objective of this paper is to explore the precise relationship between the Bethe free energy (or entropy) and the Shannon conditional entropy of graphical error correcting codes. The main result shows that the Bethe free energy…

Information Theory · Computer Science 2015-06-12 Nicolas Macris , Marc Vuffray

In a random intersection graph $G_{n,m,p}$, each of $n$ vertices selects a random subset of a set of $m$ labels by including each label independently with probability $p$ and edges are drawn between vertices that have at least one label in…

Discrete Mathematics · Computer Science 2022-10-06 Filippos Christodoulou , Sotiris Nikoletseas , Christoforos Raptopoulos , Paul Spirakis

We demonstrate that quantum correlations can emerge from the statistical correlations of random discrete models, without an a priori assumption that the random models are quantum mechanical in nature, that is without considering…

Disordered Systems and Neural Networks · Physics 2023-05-05 Ioannis Kleftogiannis , Ilias Amanatidis

We prove three new lower bounds for graph connectivity in the $1$-bit broadcast congested clique model, BCC$(1)$. First, in the KT-$0$ version of BCC$(1)$, in which nodes are aware of neighbors only through port numbers, we show an…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-05-23 Shreyas Pai , Sriram V. Pemmaraju

Random Quantum States are presently of interest in the fields of quantum information theory and quantum chaos. Moreover, a detailed study of their properties can shed light on some foundational issues of the quantum statistical mechanics…

Quantum Physics · Physics 2010-01-07 Barbara Fresch , Giorgio J. Moro

Due to their conceptual and mathematical simplicity, Erd\"os-R\'enyi or classical random graphs remain as a fundamental paradigm to model complex interacting systems in several areas. Although condensation phenomena have been widely…

Disordered Systems and Neural Networks · Physics 2019-07-16 Fernando L. Metz , Isaac Pérez Castillo

We introduce a new concept of a subgraph class called a superbubble for analyzing assembly graphs, and propose an efficient algorithm for detecting it. Most assembly algorithms utilize assembly graphs like the de Bruijn graph or the overlap…

Data Structures and Algorithms · Computer Science 2013-08-02 Taku Onodera , Kunihiko Sadakane , Tetsuo Shibuya

We give sufficient conditions under which a random graph with a specified degree sequence is symmetric or asymmetric. In the case of bounded degree sequences, our characterisation captures the phase transition of the symmetry of the random…

Combinatorics · Mathematics 2020-04-07 Lochlan Brick , Pu Gao , Angus Southwell

A generic class of scalar active matter, characterized at the mean field level by the diffusivity vanishing above some threshold density, was recently introduced [Golestanian R 2019 Phys. Rev. E 100 010601(R)]. In the presence of harmonic…

Statistical Mechanics · Physics 2020-08-26 Benoît Mahault , Ramin Golestanian

In this paper we consider the Erd\H{o}s-R\'enyi random graph in the sparse regime in the limit as the number of vertices $n$ tends to infinity. We are interested in what this graph looks like when it contains many triangles, in two…

Probability · Mathematics 2026-01-27 Suman Chakraborty , Remco van der Hofstad , Frank den Hollander

Given a dynamic network, where edges appear and disappear over time, we are interested in finding sets of edges that have similar temporal behavior and form a dense subgraph. Formally, we define the problem as the enumeration of the maximal…

Social and Information Networks · Computer Science 2021-03-02 Giulia Preti , Polina Rozenshtein , Aristides Gionis , Yannis Velegrakis

We consider the algorithmic problem of finding large \textit{balanced} independent sets in sparse random bipartite graphs, and more generally the problem of finding independent sets with specified proportions of vertices on each side of the…

Data Structures and Algorithms · Computer Science 2023-07-27 Will Perkins , Yuzhou Wang

Aligning a sequence to a walk in a labeled graph is a problem of fundamental importance to Computational Biology. For finding a walk in an arbitrary graph with $|E|$ edges that exactly matches a pattern of length $m$, a lower bound based on…

Data Structures and Algorithms · Computer Science 2022-02-01 Daniel Gibney , Sharma V. Thankachan , Srinivas Aluru

Autoencoders, as a dimensionality reduction technique, have been recently applied to outlier detection. However, neural networks are known to be vulnerable to overfitting, and therefore have limited potential in the unsupervised outlier…

Machine Learning · Computer Science 2019-10-23 Hamed Sarvari , Carlotta Domeniconi , Bardh Prenkaj , Giovanni Stilo

We consider the edge-triangle model, a two-parameter family of exponential random graphs in which dependence between edges is introduced through triangles. In the so-called replica symmetric regime, the limiting free energy exists together…

Probability · Mathematics 2023-01-31 Alessandra Bianchi , Francesca Collet , Elena Magnanini