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We investigate the probability density of rescaled sum of iterates of sine-circle map within quasi-periodic route to chaos. When the dynamical system is strongly mixing (i.e., ergodic), standard Central Limit Theorem (CLT) is expected to be…

Statistical Mechanics · Physics 2015-05-18 Ozgur Afsar , Ugur Tirnakli

This paper studies particle propagation in a one-dimensional inhomogeneous medium where the laws of motion are generated by chaotic and deterministic local maps. Assuming that the particle's initial location is random and uniformly…

Probability · Mathematics 2011-10-18 Lasse Leskelä , Mikko Stenlund

In this paper we examine the deviations from Gaussianity for two types of random variable converging to a normal distribution, namely sums of random variables generated by a deterministic discrete time map and a linearly damped variable…

Chaotic Dynamics · Physics 2020-02-19 Jeroen Wouters

It has been argued in [EPL {\bf 90} (2010) 50004], entitled {\it Essential discreteness in generalized thermostatistics with non-logarithmic entropy}, that "continuous Hamiltonian systems with long-range interactions and the so-called…

Statistical Mechanics · Physics 2017-08-23 A. Plastino , M. C. Rocca

We describe a general strategy, PERM (Pruned-Enriched Rosenbluth Method), for sampling configurations from a given Gibbs-Boltzmann distribution. The method is not based on the Metropolis concept of establishing a Markov process whose…

Soft Condensed Matter · Physics 2007-05-23 P. Grassberger , und H. Frauenkron

A finite range interacting particle system on a transitive graph is considered. Assuming that the dynamics and the initial measure are invariant, the normalized empirical distribution process converges in distribution to a centered…

Mathematical Physics · Physics 2007-05-23 Paul Doukhan , Gabriel Lang , Sana Louhichi , Bernard Ycart

In this paper, we develop a general approach to proving global and local uniform limit theorems for the Horvitz-Thompson empirical process arising from complex sampling designs. Global theorems such as Glivenko-Cantelli and Donsker…

Statistics Theory · Mathematics 2019-05-31 Qiyang Han , Jon A. Wellner

After having introduced the notion of universality in statistical mechanics and its importance for our comprehension of the macroscopic behavior of interacting systems, I review recent progress in the understanding of the scaling limit of…

Mathematical Physics · Physics 2021-11-01 Alessandro Giuliani

The Central Limit Theorem does not hold for strongly correlated stochastic variables, as is the case for statistical systems close to criticality. Recently, the calculation of the probability distribution function (PDF) of the magnetization…

Statistical Mechanics · Physics 2025-03-28 Sankarshan Sahu , Bertrand Delamotte , Adam Rançon

We study in limit law the complexity of some anticipated rejection random sampling algorithms. We express this complexity in terms of a probabilistic process, the threshold sum process. We show that, under the right conditions, the…

Combinatorics · Mathematics 2015-08-25 Axel Bacher , Andrea Sportiello

We derive a systematic, multiple time-scale perturbation expansion for the work distribution in isothermal quasi-static Langevin processes. To first order we find a Gaussian distribution reproducing the result of Speck and Seifert [Phys.…

Statistical Mechanics · Physics 2015-06-15 Johannes Hoppenau , Andreas Engel

We consider transport in two billiard models, the infinite horizon Lorentz gas and the stadium channel, presenting analytical results for the spreading packet of particles. We first obtain the cumulative distribution function of traveling…

Statistical Mechanics · Physics 2019-11-06 Lior Zarfaty , Alexander Peletskyi , Eli Barkai , Sergey Denisov

Parvan [arXiv:0911.0383v1] [1] has recently presented some calculations in order to demonstrate the incorrectness of the results obtained from the generalized multinomial coefficients (GMC) presented in Ref. [2]. According to Parvan, the…

Statistical Mechanics · Physics 2010-09-30 Thomas Oikonomou

Deep generative models are routinely used in generating samples from complex, high-dimensional distributions. Despite their apparent successes, their statistical properties are not well understood. A common assumption is that with enough…

Machine Learning · Statistics 2025-01-15 Edric Tam , David B. Dunson

The central limit theorem provides the theoretical foundation for the universality of the normal distribution: under broad conditions, the asymptotic distribution of a sum of independent random variables approaches a Gaussian. Yet, physical…

Data Analysis, Statistics and Probability · Physics 2026-03-26 Mario Castro , José A. Cuesta

The central limit theorem ensures that a sum of random variables tends to a Gaussian distribution as their total number tends to infinity. However, for a class of positive random variables, we find that the sum tends faster to a log-normal…

Fluid Dynamics · Physics 2013-10-16 H. Mouri

In an earlier work we had considered a Gaussian ensemble of random matrices in the presence of a given external matrix source. The measure is no longer unitary invariant and the usual techniques based on orthogonal polynomials, or on the…

Statistical Mechanics · Physics 2009-10-31 E. Brezin , S. Hikami

Rosenfeld [Phys. Rev. A 15, 2545 (1977)] noticed that casting transport coefficients of simple monatomic, equilibrium fluids in specific dimensionless forms makes them approximately single-valued functions of excess entropy. This has…

Central limit theorems for random walks in quenched random environments have attracted plenty of attention in the past years. More recently still, finer local limit theorems -- yielding a Gaussian density multiplied by a highly oscillatory…

Probability · Mathematics 2013-03-07 Mikko Stenlund

In the study of natural and artificial complex systems, responses that are not completely determined by the considered decision variables are commonly modelled probabilistically, resulting in response distributions varying across decision…

Methodology · Statistics 2021-10-07 Athénaïs Gautier , David Ginsbourger , Guillaume Pirot