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Related papers: Correlations in random cluster model at $q=1$

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We study percolation and the random cluster model on the triangular lattice with 3-body interactions. Starting with percolation, we generalize the star--triangle transformation: We introduce a new parameter (the 3-body term) and identify…

Statistical Mechanics · Physics 2009-11-11 L. Chayes , H. K. Lei

Herein, we propose a site random cluster model by introducing an additional cluster weight in the partition function of the traditional site percolation. To simulate the model on a square lattice, we combine the color-assignation and the…

Statistical Mechanics · Physics 2015-08-26 Songsong Wang , Yuan Yang , Wanzhou Zhang , Chengxiang Ding

The random-cluster model is a dependent percolation model that has applications in the study of Ising and Potts models. In this paper, several new results are obtained for the random-cluster model on nonamenable graphs with cluster…

Probability · Mathematics 2007-05-23 Olle Haggstrom , Johan Jonasson , Russell Lyons

The article investigates the possibility of measuring the strength of a linear correlation relationship between nominal data and numerical data. Correlation coefficients for variables coded with real numbers as well as for variables coded…

Machine Learning · Computer Science 2023-02-07 Zenon Gniazdowski

We study the scenario of graph-based clustering algorithms such as spectral clustering. Given a set of data points, one first has to construct a graph on the data points and then apply a graph clustering algorithm to find a suitable…

Machine Learning · Statistics 2011-02-11 Markus Maier , Ulrike von Luxburg , Matthias Hein

This paper introduces a method for studying the correlation structure of a range of responses modelled by a multivariate generalised linear mixed model (MGLMM). The methodology requires the existence of clusters of observations and that…

Methodology · Statistics 2021-08-02 Jeanett S. Pelck , Rodrigo Labouriau

An ensemble consisting on systems of two entangled spin 1/2 particles, all of them in the same global quantum state, are considered. The two spins are measured, each of them, on a fixed direction, at two randomly selected measurement times.…

Quantum Physics · Physics 2015-03-06 Ramon Lapiedra , A. Pérez

Linearizing the Heisenberg equations of motion around the ground state of an interacting quantum many-body system, one gets a time-evolution generator in the positive cone of a real symplectic Lie algebra. The presence of disorder in the…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 T. Lueck , H. -J. Sommers , M. R. Zirnbauer

Breaking of equivalence between the microcanonical ensemble and the canonical ensemble, describing a large system subject to hard and soft constraints, respectively, was recently shown to occur in large random graphs. Hard constraints must…

Probability · Mathematics 2017-06-06 Diego Garlaschelli , Frank den Hollander , Andrea Roccaverde

Fixed effects models are very flexible because they do not make assumptions on the distribution of effects and can also be used if the heterogeneity component is correlated with explanatory variables. A disadvantage is the large number of…

Methodology · Statistics 2015-12-17 Moritz Berger , Gerhard Tutz

We study a special inhomogeneous quantum network consisting of a ring of $M$ pseudo-spins (here $M = 4$) sequentially coupled to one and the same central spin under the influence of given pulse sequences (quantum gate operations). This…

Quantum Physics · Physics 2007-05-23 Guenter Mahler , Ilki Kim

Clustering evaluation measures are frequently used to evaluate the performance of algorithms. However, most measures are not properly normalized and ignore some information in the inherent structure of clusterings. We model the relation…

Machine Learning · Computer Science 2012-09-05 Qiaoliang Xiang , Qi Mao , Kian Ming Chai , Hai Leong Chieu , Ivor Tsang , Zhendong Zhao

In this paper, we study the $\alpha$-cluster tree ($\alpha$-tree) under both singular and nonsingular measures. The $\alpha$-tree uses probability contents within a level set to construct a cluster tree so that it is well-defined for…

Statistics Theory · Mathematics 2018-07-12 Yen-Chi Chen

We study two related probabilistic models of permutations and trees biased by their number of descents. Here, a descent in a permutation $\sigma$ is a pair of consecutive elements $\sigma(i), \sigma(i+1)$ such that $\sigma(i) >…

Probability · Mathematics 2023-12-19 Paul Thévenin , Stephan Wagner

Correlation clustering is arguably the most natural formulation of clustering. Given n objects and a pairwise similarity measure, the goal is to cluster the objects so that, to the best possible extent, similar objects are put in the same…

Data Structures and Algorithms · Computer Science 2020-02-27 David García-Soriano , Konstantin Kutzkov , Francesco Bonchi , Charalampos Tsourakakis

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

Quantum correlations are the singular, defining resource of quantum information science and metrology, forming the basis of every operational advantage that quantum systems hold over classical ones. Yet exact bounds on these…

Quantum Physics · Physics 2025-12-22 Samuel Alperin

We propose an information-theoretical measure, the \textit{relative cluster entropy} $\mathcal{D_{C}}[P \| Q] $, to discriminate among cluster partitions characterised by probability distribution functions $P$ and $Q$. The measure is…

Statistical Mechanics · Physics 2022-10-05 A. Carbone , L. Ponta

We introduce a new model of correlated randomly growing graphs and study the fundamental questions of detecting correlation and estimating aspects of the correlated structure. The model is simple and starts with any model of randomly…

Probability · Mathematics 2020-04-29 Miklos Z. Racz , Anirudh Sridhar

We generalize finite-sample bounds for convex clustering to the setting where affinity weights appearing in the objective correspond to a general connected graph. These bounds and their analysis lead to a better understanding of clustering…

Machine Learning · Statistics 2026-05-26 Sam Rosen , Jason Xu
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