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For random percolation at p_c, the probability distribution P(n) of the number of spanning clusters (n) has been studied in large scale simulations. The results are compatible with $P(n) \sim \exp(-an^2)$ for all dimensions. We also study…

Statistical Mechanics · Physics 2009-10-30 Parongama Sen

Zero- and two-dimensional crystal defects form in open statistical ensembles, such as the grand canonical, that are usually inaccessible with conventional simulation techniques. This longstanding challenge is overcome with a new Hamiltonian…

Materials Science · Physics 2026-01-16 Flynn Walsh , Babak Sadigh , Joseph T. McKeown , Timofey Frolov

We consider independent and $m$-dependent two-dimensional oriented site percolation with open-site density close to one started from Bernoulli product measures. We show that the probability of an occupied interval in the former process…

Probability · Mathematics 2020-11-24 Achillefs Tzioufas

Percolation on a plane is usually associated with clusters spanning two opposite sides of a rectangular system. Here we investigate three-leg clusters generated on a square lattice and spanning the three sides of equilateral triangles. If…

Statistical Mechanics · Physics 2022-04-15 Zbigniew Koza

This work proposes a novel technique for the numerical calculus of the fractal dimension of fractal objects which can be represented as a closed contour. The proposed method maps the fractal contour onto a complex signal and calculates its…

Data Analysis, Statistics and Probability · Physics 2012-01-17 João B. Florindo , Odemir M. Bruno

Markov chain Monte Carlo (MCMC) methods are a very versatile and widely used tool to compute integrals and expectations. In this short survey we focus on error bounds, rules for choosing the burn in, high dimensional problems and…

Statistics Theory · Mathematics 2014-12-03 Erich Novak , Daniel Rudolf

We introduce for canonical fragmention models an exact method for computing expectation values which exclude the largest cluster. This method allows for the computation of the reduced multiplicity and other quantities of interest introduced…

Nuclear Theory · Physics 2009-09-25 K. C. Chase , A. Z. Mekjian

In this paper, a Monte Carlo based approach for the quantification of the importance of the scattering input parameters with respect to the failure probability is presented. Using the basic idea of the alpha-factors of the First Order…

Computation · Statistics 2024-08-14 Thomas Most

In this article we explore how structural parameters of composites filled with one-dimensional, electrically conducting elements (such as sticks, needles, chains, or rods) affect the percolation properties of the system. To this end, we…

Soft Condensed Matter · Physics 2014-05-06 J. L. Mietta , R. M. Negri , P. I. Tamborenea

Multivariate circular observations, i.e. points on a torus are nowadays very common. Multivariate wrapped models are often appropriate to describe data points scattered on p-dimensional torus. However, statistical inference based on this…

Computation · Statistics 2018-11-16 Anahita Nodehi , Mousa Golalizadeh , Mehdi Maadooliat , Claudio Agostinelli

Quasi-Monte Carlo sampling can attain far better accuracy than plain Monte Carlo sampling. However, with plain Monte Carlo sampling it is much easier to estimate the attained accuracy. This article describes methods old and new to quantify…

Numerical Analysis · Mathematics 2025-07-16 Art B. Owen

This work is the first in a series of papers devoted to the construction and study of scaling limits of dynamical and near-critical planar percolation and related objects like invasion percolation and the Minimal Spanning Tree. We show here…

Probability · Mathematics 2014-02-17 Christophe Garban , Gábor Pete , Oded Schramm

Monte Carlo integration is a commonly used technique to compute intractable integrals and is typically thought to perform poorly for very high-dimensional integrals. To show that this is not always the case, we examine Monte Carlo…

Methodology · Statistics 2023-05-26 Yanbo Tang

Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other…

Methodology · Statistics 2014-11-20 Patrick K. Kimes , Yufeng Liu , D. Neil Hayes , J. S. Marron

In this manuscript, we describe a new configurational bias Monte Carlo technique for the simulation of peptides. We focus on the biologically relevant cases of linear and cyclic peptides. Our approach leads to an efficient,…

Soft Condensed Matter · Physics 2015-06-25 Michael W. Deem , Joel Bader

Sequential Monte Carlo (SMC) algorithms represent a suite of robust computational methodologies utilized for state estimation and parameter inference within dynamical systems, particularly in real-time or online environments where data…

The statistical precision of a chord method for estimating fractal dimension from a correlation integral is derived. The optimal chord length is determined, and a comparison is made to other estimators. These calculations use the…

comp-gas · Physics 2019-06-05 James Theiler , Turab Lookman

By molecular dynamics simulations and free energy calculations based on Monte Carlo method, the detailed balance between Pt cluster isomers was investigated. For clusters of n<=50, stationary equilibrium is achieved in 100 ns in the…

Chemical Physics · Physics 2014-12-16 Zheng-Zhe Lin

It is shown that fractal dimension can be estimated seeking a solution of functional equation defined for areas of coverages of different scales. The method proposed is compared with widely known way to estimate fractal dimension via linear…

Chaotic Dynamics · Physics 2021-03-16 Dmitry Zhabin

We design and implement a novel algorithm for computing a multilevel Monte Carlo (MLMC) estimator of the cumulative distribution function of a quantity of interest in problems with random input parameters or initial conditions. Our approach…

Numerical Analysis · Mathematics 2020-08-26 Søren Taverniers , Daniel M. Tartakovsky
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