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Related papers: Scaling function for self-avoiding polygons

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The analysis of correlation function data obtained by Monte Carlo simulations of the two-dimensional 4-state Potts model, XY model, and self-dual disordered Ising model at criticality are presented. We study the logarithmic corrections to…

Statistical Mechanics · Physics 2009-11-10 Bertrand Berche , Lev Shchur

We examine self-avoiding walks in dimensions 4 to 8 using high-precision Monte-Carlo simulations up to length N=16384, providing the first such results in dimensions $d > 4$ on which we concentrate our analysis. We analyse the scaling…

Statistical Mechanics · Physics 2009-11-07 Aleksander L. Owczarek , Thomas Prellberg

We consider the estimation of the value of a linear functional of the slope parameter in functional linear regression, where scalar responses are modeled in dependence of random functions. The theory in this paper covers in particular…

Statistics Theory · Mathematics 2011-12-19 J. Johannes , R. Schenk

The $n$-vector spin model, which includes the self-avoiding walk (SAW) as a special case for the $n \rightarrow 0 $ limit, has an upper critical dimensionality at four spatial dimensions (4D). We simulate the SAW on 4D hypercubic lattices…

Statistical Mechanics · Physics 2021-12-14 Sheng Fang , Youjin Deng , Zongzheng Zhou

We use new algorithms, based on the finite lattice method of series expansion, to extend the enumeration of self-avoiding walks and polygons on the triangular lattice to length 40 and 60, respectively. For self-avoiding walks to length 40…

Statistical Mechanics · Physics 2009-11-10 Iwan Jensen

In this work a symmetry of universal finite-size scaling functions under a certain anisotropic scale transformation is postulated. This transformation connects the properties of a finite two-dimensional system at criticality with…

Statistical Mechanics · Physics 2009-11-07 Alfred Hucht

Regressing a scalar response on a random function is nowadays a common situation. In the nonparametric setting, this paper paves the way for making the local linear regression based on a projection approach a prominent method for solving…

Methodology · Statistics 2019-07-19 Frédéric Ferraty , Stanislav Nagy

We consider the estimation of the value of a linear functional of the slope parameter in functional linear regression, where scalar responses are modeled in dependence of random functions. In Johannes and Schenk [2010] it has been shown…

Statistics Theory · Mathematics 2011-12-14 Jan Johannes , Rudolf Schenk

Multiplicative logarithmic corrections frequently characterize critical behaviour in statistical physics. Here, a recently proposed theory relating the exponents of such terms is extended to account for circumstances which often occur when…

Statistical Mechanics · Physics 2009-11-11 R. Kenna , D. A. Johnston , W. Janke

This article presents an empirical validation of the functional multidimensional scaling model, a novel approach that improves the smoothness of time-varying dissimilarities in a low-dimensional space, embedding a modified Adam stochastic…

Applications · Statistics 2025-05-21 Liting Li

We describe a method for approximating the universal scaling functions for the Ising model in a field. By making use of parametric coordinates, the free energy scaling function has a polynomial series everywhere. Its form is taken to be a…

Statistical Mechanics · Physics 2021-10-29 Jaron Kent-Dobias , James P. Sethna

A method for determining the generalised scaling function(s) arising in the high spin behaviour of long operator anomalous dimensions in the planar $sl(2)$ sector of ${\cal N}=4$ SYM is proposed. The all-order perturbative expansion around…

High Energy Physics - Theory · Physics 2009-12-15 Davide Fioravanti , Paolo Grinza , Marco Rossi

An explicit expression is derived for the scattering function of a self-avoiding polymer chain in a $d$-dimensional space. The effect of strength of segment interactions on the shape of the scattering function and the radius of gyration of…

Statistical Mechanics · Physics 2007-05-23 A. D. Drozdov

Estimation is the computational task of recovering a hidden parameter $x$ associated with a distribution $D_x$, given a measurement $y$ sampled from the distribution. High dimensional estimation problems arise naturally in statistics,…

Data Structures and Algorithms · Computer Science 2019-08-07 Prasad Raghavendra , Tselil Schramm , David Steurer

A key goal in the design of probabilistic inference algorithms is identifying and exploiting properties of the distribution that make inference tractable. Lifted inference algorithms identify symmetry as a property that enables efficient…

Artificial Intelligence · Computer Science 2019-07-02 Steven Holtzen , Todd Millstein , Guy Van den Broeck

We present a new unified theory of critical finite-size scaling for lattice statistical mechanical models with periodic boundary conditions above the upper critical dimension. Our theory is based on recent mathematically rigorous results…

Statistical Mechanics · Physics 2026-03-02 Yucheng Liu , Jiwoon Park , Gordon Slade

The extension of the classical Bayesian penalized spline method to inference on vector-valued functions is considered, with an emphasis on characterizing the suitability of the method for general application.We show that the standard…

Machine Learning · Statistics 2010-03-26 David M. Rogers , Thomas L. Beck

Recent advances in boundary critical phenomena have led to the discovery of a new surface universality class in the three-dimensional $O(N)$ model. The newly found ``extraordinary-log" phase can be realized on a two-dimensional surface for…

Statistical Mechanics · Physics 2025-04-17 Francesco Parisen Toldin , Abijith Krishnan , Max A. Metlitski

For systems in the universality class of the three-dimensional Ising model we compute the critical exponents in the local potential approximation (LPA), that is, in the framework of the Wegner-Houghton equation. We are mostly interested in…

High Energy Physics - Lattice · Physics 2015-06-25 M. M. Tsypin

Motivated by numerical methods for solving parametric partial differential equations, this paper studies the approximation of multivariate analytic functions by algebraic polynomials. We introduce various anisotropic model classes based on…

Numerical Analysis · Mathematics 2020-01-17 Andrea Bonito , Ronald DeVore , Diane Guignard , Peter Jantsch , Guergana Petrova