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To reach a deeper understanding of fluid interfaces it is necessary to identify a meaningful coarse-graining length that separates intrinsic fluctuations from capillary ones, given the lack of a proper statistical mechanical definition of…

Soft Condensed Matter · Physics 2022-01-05 György Hantal , Pál Jedlovszky , Marcello Sega

Scaling, hyperscaling and finite-size scaling were long considered problematic in theories of critical phenomena in high dimensions. The scaling relations themselves form a model-independent structure that any model-specific theory must…

Statistical Mechanics · Physics 2024-05-29 Ralph Kenna , Bertrand Berche

Classically, percolation critical exponents are linked to the power laws that characterize percolation cluster fractal properties. It is found here that the gradient percolation power laws are conserved even for extreme gradient values for…

Disordered Systems and Neural Networks · Physics 2007-05-23 A. Desolneux , B. Sapoval

The percolation transitions on hyperbolic lattices are investigated numerically using finite-size scaling methods. The existence of two distinct percolation thresholds is verified. At the lower threshold, an unbounded cluster appears and…

Statistical Mechanics · Physics 2009-11-13 Seung Ki Baek , Petter Minnhagen , Beom Jun Kim

Transient dynamics leading to the synchrony of pulse-coupled oscillators has previously been studied as an aggregation process of synchronous clusters, and a rate equation for the cluster size distribution has been proposed. However, the…

Statistical Mechanics · Physics 2023-03-06 Gangyong Gwon , Young Sul Cho

Percolation has long served as a model for diverse phenomena and systems. The percolation transition, that is, the formation of a giant cluster on a macroscopic scale, is known as one of the most robust continuous transitions. Recently,…

Statistical Mechanics · Physics 2016-12-08 Deokjae Lee , Young Sul Cho , Byungnam Kahng

We study the percolation properties of geometrical clusters defined in the overlap space of two statistically independent replicas of a square-lattice Ising model that are simulated at the same temperature. In particular, we consider two…

Statistical Mechanics · Physics 2024-02-23 Michail Akritidis , Nikolaos G. Fytas , Martin Weigel

Independent random signs can govern various discrete models that converge to non-isomorphic continuous limits. Convergence of Fourier-Walsh spectra is established under appropriate conditions.

Probability · Mathematics 2007-05-23 Boris Tsirelson

We consider the isotropic two-dimensional abelian sandpile model from a perspective based on two-dimensional (conformal) field theory. We compute lattice correlation functions for various cluster variables (at and off criticality), from…

High Energy Physics - Theory · Physics 2009-11-07 S. Mahieu , P. Ruelle

We give several algebraic bounds for percolation on directed and undirected graphs: proliferation of strongly-connected clusters, proliferation of in- and out-clusters, and the transition associated with the number of giant components.

Mathematical Physics · Physics 2015-03-03 Kathleen E. Hamilton , Leonid P. Pryadko

Recent Monte Carlo simulations of the critical point of the restricted primitive model for ionic solutions are reported. Only the continuum version of the model is considered. A finite size scaling analysis based in the Bruce-Wilding…

Statistical Mechanics · Physics 2007-05-23 Jean-Michel Caillol

We study limit laws for simple random walks on supercritical long-range percolation clusters on the integer lattice. For the long range percolation model, the probability that two vertices are connected behaves asymptotically as a negative…

Probability · Mathematics 2024-05-31 Noam Berger , Yuki Tokushige

The partition function of the finite $1+\epsilon$ state Potts model is shown to yield a closed form for the distribution of clusters in the immediate vicinity of the percolation transition. Various important properties of the transition are…

Statistical Mechanics · Physics 2009-10-30 Joseph Rudnick , Paisan Nakmahachalasint , George Gaspari

It is well know that systems with an interaction decaying as a power of the distance may have critical exponents that are different from those of short-range systems. The boundary between long-range and short-range is known, however the…

Statistical Mechanics · Physics 2014-12-30 Edouard Brezin , Giorgio Parisi , Federico Ricci-Tersenghi

By analogy with Carleson's observation on Cardy's formula describing crossing probabilities for the scaling limit of critical percolation, we exhibit ``privileged geometries'' for Stochastic Loewner Evolutions with various parameters, for…

Probability · Mathematics 2007-05-23 Julien Dubedat

Short distance scaling limits of a class of integrable models on two-dimensional Minkowski space are considered in the algebraic framework of quantum field theory. Making use of the wedge-local quantum fields generating these models, it is…

Mathematical Physics · Physics 2012-01-06 Henning Bostelmann , Gandalf Lechner , Gerardo Morsella

Percolation is a concept widely used in many fields of research and refers to the propagation of substances through porous media (e.g., coffee filtering), or the behaviour of complex networks (e.g., spreading of diseases). Percolation…

Soft Condensed Matter · Physics 2015-12-02 Wolf B. Dapp , Martin H. Müser

We investigate the dependence of cluster abundance $n(>M,r_{cl})$, i.e., the number density of clusters with mass larger than $M$ within radius $r_{cl}$, on scale parameter $r_{cl}$. Using numerical simulations of clusters in the CDM…

Astrophysics · Physics 2009-10-30 Wen Xu , Li-Zhi Fang , Xiang-Ping Wu

A binary liquid near its consolute point exhibits critical fluctuations of the local composition; the diverging correlation length has always challenged simulations. The method of choice for the calculation of critical points in the phase…

Statistical Mechanics · Physics 2021-04-29 Yogyata Pathania , Dipanjan Chakraborty , Felix Höfling

Deep neural networks exhibit empirical neural scaling laws, with error decreasing as a power law with increasing model or data size, across a wide variety of architectures, tasks, and datasets. This universality suggests that scaling laws…

Machine Learning · Computer Science 2024-12-12 Ari Brill
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