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Symmetry breaking for graphs and other combinatorial objects is notoriously hard. On the one hand, complete symmetry breaks are exponential in size. On the other hand, current, state-of-the-art, partial symmetry breaks are often considered…

Logic in Computer Science · Computer Science 2026-04-01 Michael Codish , Mikoláš Janota

We deal with a random graph model where at each step, a vertex is chosen uniformly at random, and it is either duplicated or its edges are deleted. Duplication has a given probability. We analyse the limit distribution of the degree of a…

Probability · Mathematics 2014-09-19 Ágnes Backhausz , Tamás F. Móri

We consider the multi-parameter random simplicial complex as a higher dimensional extension of the classical Erd\"os-R\'enyi graph. We investigate appearance of "unusual" topological structures in the complex from the point of view of large…

Probability · Mathematics 2022-02-18 Gennady Samorodnitsky , Takashi Owada

Here we review the approach to glassy systems based on the replica method and we introduce the main ingredients of replica symmetry breaking. We explain why the replica method has been successful in spin glass and why it should be…

Disordered Systems and Neural Networks · Physics 2008-02-03 Giorgio Parisi

In this paper, we present a novel approach based on the random walk process for finding meaningful representations of a graph model. Our approach leverages the transient behavior of many short random walks with novel initialization…

Social and Information Networks · Computer Science 2018-05-14 Lin Li , William M. Campbell , Rajmonda S. Caceres

The randomly pinned planar flux line array is supposed to show a phase transition to a vortex glass phase at low temperatures. This transition has been examined by using a mapping onto a 2D XY-model with random an\-iso\-tropy but without…

Condensed Matter · Physics 2016-08-31 Jan Kierfeld

We consider mean-field vector spin glasses with possibly non-convex interactions. Up to a small perturbation of the parameters defining the model, the asymptotic behavior of the Gibbs measure is described in terms of a critical point of an…

Probability · Mathematics 2026-01-06 Hong-Bin Chen , Jean-Christophe Mourrat

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

We study the random-link matching problem on random regular graphs, alongside with two relaxed versions of the problem, namely the fractional matching and the so-called "loopy" fractional matching. We estimated the asymptotic average…

Disordered Systems and Neural Networks · Physics 2020-03-16 Giorgio Parisi , Gianmarco Perrupato , Gabriele Sicuro

For data sets populated by a very well modeled process and by another process of unknown probability density function (PDF), a desired feature when manipulating the fraction of the unknown process (either for enhancing it or suppressing it)…

Machine Learning · Statistics 2017-04-05 Pietro Vischia , Tommaso Dorigo

In the context of random regular graphs, the size of the maximum cut is probably the second most studied graph parameter after the independence ratio. Zdeborov\'a and Boettcher used the cavity method, a non-rigorous statistical physics…

Combinatorics · Mathematics 2025-06-27 Viktor Harangi

A new powerful method to test the stability of the replica symmetric spin glass phase is proposed by introducing a replicon generator function g(v). Exact symmetry arguments are used to prove that its extremum is proportional to the inverse…

Disordered Systems and Neural Networks · Physics 2007-05-23 T. Temesvari

We consider classical spin systems evolving in continuous time with interactions given by a locally tree-like graph. Several approximate analysis methods have earlier been reported based on the idea of Belief Propagation / cavity method. We…

Statistical Mechanics · Physics 2023-04-19 Erik Aurell , David Machado Perez , Roberto Mulet

A random vector whose norm and overlap (inner product with an independent copy) concentrates is shown to have random low-dimensional projections that are approximately random Gaussians. Conversely, asymptotically random Gaussian projections…

Probability · Mathematics 2025-12-23 Timothy L. H. Wee , Sekhar Tatikonda

Parametric resampling schemes have been recently introduced in complex network analysis with the aim of assessing the statistical significance of graph clustering and the robustness of community partitions. We propose here a method to…

Physics and Society · Physics 2014-02-25 Fabrizio De Vico Fallani , Vincenzo Nicosia , Vito Latora , Mario Chavez

Using the theory of negative association for measures and the notion of random weak limits of sparse graphs, we establish the validity of the cavity method for counting spanning subgraphs subject to local constraints in asymptotically…

Probability · Mathematics 2011-03-21 Justin Salez

Graphs are used in many disciplines to model the relationships that exist between objects in a complex discrete system. Researchers may wish to compare a network of interest to a "typical" graph from a family (or ensemble) of graphs which…

Combinatorics · Mathematics 2025-08-08 Catherine Greenhill

We show by direct calculation that the replica and cavity methods are exactly equivalent for the spectrum of Erdos-Renyi random graph. We introduce a variational formulation based on the cavity method and use it to find approximate…

Statistical Mechanics · Physics 2011-05-26 Frantisek Slanina

Within a Kuhn-Tucker cavity method introduced in a former paper, we study optimal stability learning for situations, where in the replica formalism the replica symmetry may be broken, namely (i) the case of a simple perceptron above the…

Disordered Systems and Neural Networks · Physics 2009-10-28 F. Gerl , U. Krey

Specify a randomized algorithm that, given a very large graph or network, extracts a random subgraph. What can we learn about the input graph from a single subsample? We derive laws of large numbers for the sampler output, by relating…

Statistics Theory · Mathematics 2017-10-13 Peter Orbanz