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Related papers: Scaling function for self-avoiding polygons

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The limitations of three-dimensional semi-classical gravity are explored in the context of a conformally invariant theory for a self-interacting scalar field. The analysis of the theory's scaling behaviour reveals that scalar-loop effects…

General Relativity and Quantum Cosmology · Physics 2009-10-31 George Tsoupros

Pole Expansion and Selected Inversion (PEXSI) is an efficient scheme for evaluating selected entries of functions of large sparse matrices as required e.g. in electronic structure algorithms. We show that the triangular factorizations…

Numerical Analysis · Mathematics 2020-01-20 Simon Etter

A self-avoiding polygon is a lattice polygon consisting of a closed self-avoiding walk on a square lattice. Surprisingly little is known rigorously about the enumeration of self-avoiding polygons, although there are numerous conjectures…

Combinatorics · Mathematics 2019-08-15 Kyungpyo Hong , Seungsang Oh

We make an estimation of the support of a multivariable scaling function for an arbitrary dilation matrix. We give a method of calculating the values of the scaling function on a tight set using the knowledge of the size of the support.

Classical Analysis and ODEs · Mathematics 2008-01-03 Irina Maximenko

We determine the Lagrange function in Taylor polynomial approximation by solving an appropriate initial-value problem. Hence, we determine the remainder term which we then approximate by means of a natural cubic spline. This results in a…

Numerical Analysis · Mathematics 2023-03-06 J. S. C. Prentice

Advanced chain-growth computer simulation methodologies have been employed for a systematic statistical analysis of the critical behavior of a polymer adsorbing at a substrate. We use finitesize scaling techniques to investigate the…

Soft Condensed Matter · Physics 2017-05-09 J. A. Plascak , Paulo H. L. Martins , Michael Bachmann

We propose a method for designing accurate interpolation formulas on the real axis for the purpose of function approximation in weighted Hardy spaces. In particular, we consider the Hardy space of functions that are analytic in a strip…

Numerical Analysis · Mathematics 2016-06-17 Ken'ichiro Tanaka , Tomoaki Okayama , Masaaki Sugihara

City is proved to be a scale-free phenomenon, and spatial autocorrelation is often employed to analyze spatial redundancy of cities. Unfortunately, spatial analysis results deviated practical requirement in many cases due to fractal nature…

Physics and Society · Physics 2023-08-09 Meng Fu , Yanguang Chen

We study scaling function geometry. We show the existence of the scaling function of a geometrically finite one-dimensional mapping. This scaling function is discontinuous. We prove that the scaling function and the asymmetries at the…

Dynamical Systems · Mathematics 2008-02-03 Yunping Jiang

Some important applicative problems require the evaluation of functions $\Psi$ of large and sparse and/or \emph{localized} matrices $A$. Popular and interesting techniques for computing $\Psi(A)$ and $\Psi(A)\mathbf{v}$, where $\mathbf{v}$…

Numerical Analysis · Mathematics 2022-04-25 Daniele Bertaccini , Marina Popolizio , Fabio Durastante

We consider the class of convex minimization problems, composed of a self-concordant function, such as the $\log\det$ metric, a convex data fidelity term $h(\cdot)$ and, a regularizing -- possibly non-smooth -- function $g(\cdot)$. This…

Machine Learning · Statistics 2014-05-14 Anastasios Kyrillidis , Rabeeh Karimi Mahabadi , Quoc Tran-Dinh , Volkan Cevher

We develop a modeling framework for dynamic function-on-scalars regression, in which a time series of functional data is regressed on a time series of scalar predictors. The regression coefficient function for each predictor is allowed to…

Methodology · Statistics 2018-10-25 Daniel R. Kowal

Estimating a fractal dimension from a finite stochastic trajectory is a finite-size scaling problem: the apparent box-counting exponent is shaped by an occupancy crossover between the resolved range of scales and the finite number of…

Statistical Mechanics · Physics 2026-05-28 Bon A. Koo , Edward Ju

We derive theorems which outline explicit mechanisms by which anomalous scaling for the probability density function of the sum of many correlated random variables asymptotically prevails. The results characterize general anomalous scaling…

Statistical Mechanics · Physics 2015-05-14 Attilio L. Stella , Fulvio Baldovin

We explore and compare three approximate schemes allowing simple implementation of complex density functionals by making use of selfconsistent implementation of simpler functionals: (i) post-LDA evaluation of complex functionals at the LDA…

Accelerated algorithms for simulating the morphological evolution of strained heteroeptiaxy based on a ball and spring lattice model in three dimensions are explained. We derive exact Green's function formalisms for boundary values in the…

Statistical Mechanics · Physics 2008-02-29 Chi-Hang Lam , M. T. Lung , Leonard M. Sander

This paper considers an optimization problem for a dynamical system whose evolution depends on a collection of binary decision variables. We develop scalable approximation algorithms with provable suboptimality bounds to provide…

Optimization and Control · Mathematics 2016-10-31 Insoon Yang , Samuel A. Burden , Ram Rajagopal , S. Shankar Sastry , Claire J. Tomlin

We simulate the spin-1/2 Ising model and the Blume-Capel model at various values of the parameter D on the simple cubic lattice. We perform a finite size scaling study of lattices of a linear size up to L=360 to obtain accurate estimates…

Statistical Mechanics · Physics 2013-05-29 Martin Hasenbusch

In functional linear regression, the parameters estimation involves solving a non necessarily well-posed problem and it has points of contact with a range of methodologies, including statistical smoothing, deconvolution and projection on…

Statistics Theory · Mathematics 2018-01-04 Andrea Ghiglietti , Francesca Ieva , Anna Maria Paganoni , Giacomo Aletti

We study the feature-scaled version of the Monte Carlo algorithm with linear function approximation. This algorithm converges to a scale-invariant solution, which is not unduly affected by states having feature vectors with large norms. The…

Machine Learning · Computer Science 2022-05-31 Rahul Madhavan , Hemanta Makwana