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We consider Vlasov-type scaling for Markov evolution of birth-and-death type in continuum, which is based on a proper scaling of corresponding Markov generators and has an algorithmic realization in terms of related hierarchical chains of…

Functional Analysis · Mathematics 2015-01-27 Dmitri Finkelshtein , Yuri Kondratiev , Oleksandr Kutoviy

Compositional data arise in many real-life applications and versatile methods for properly analyzing this type of data in the regression context are needed. When parametric assumptions do not hold or are difficult to verify, non-parametric…

Methodology · Statistics 2023-09-07 Michail Tsagris , Abdulaziz Alenazi , Connie Stewart

We present the first experimental observations of scale-free behavior in the bubble footprint distribution during the boiling crisis of water, in pool and flow boiling conditions. We formulate a continuum percolation model that elucidates…

Fluid Dynamics · Physics 2019-04-10 Limiao Zhang , Jee Hyun Seong , Matteo Bucci

A thorough discussion of the statistical ensemble of scale-free connected random tree graphs is presented. Methods borrowed from field theory are used to define the ensemble and to study analytically its properties. The ensemble is…

Statistical Mechanics · Physics 2009-11-07 Z. Burda , J. D. Correia , A. Krzywicki

We conduct athermal simulations of freely-cooling, viscous soft spheres around the jamming transition density \phi_{J}, and find evidence for a growing length \xi(t) that governs relaxation to mechanical equilibrium. \xi(t) is manifest in…

Soft Condensed Matter · Physics 2009-11-13 D. A. Head

The notions of self-organised criticality (SOC) and turbulence are traditionally considered to be applicable to disjoint classes of phenomena. Nevertheless, scale-free burst statistics is a feature shared by turbulent as well as…

We develop a scaling theory of the unjamming transition of soft frictionless disks in two dimensions by defining local areas, which can be uniquely assigned to each contact. These serve to define local order parameters, whose distribution…

Disordered Systems and Neural Networks · Physics 2017-03-29 Kabir Ramola , Bulbul Chakraborty

In the recent [3], Cesbron and Herda study a Vlasov-Fokker-Planck (VFP) equation with non-symmetric interaction, introduced in physics to model the distribution of electrons in a synchrotron particle accelerator. We make four remarks in…

Probability · Mathematics 2023-11-13 Pierre Monmarché

Evolution of the scale factor a(t) in Friedmann models (those with zero pressure and a constant cosmological term Lambda) is well understood, and elegantly summarized in the review of Felten and Isaacman [Rev. Mod. Phys. 58, 689 (1986)].…

Astrophysics · Physics 2008-11-26 J. M. Overduin , F. I. Cooperstock

In the recent paper [I.M.Suslov, JETP {\bf 114} (2012) 107] a new scaling theory of electron localization was proposed. We show that numerical data for the quasi-one dimensional Anderson model do not support predictions of this theory.

Disordered Systems and Neural Networks · Physics 2015-06-05 Peter Markos

The description of complex physical phenomena often involves sophisticated models that rely on a large number of parameters, with many dimensions and scales. One practical way to simplify that kind of models is to discard some of the…

Soft Condensed Matter · Physics 2025-11-11 Simone Rusconi , Christina Schenk , Razvan Ceuca , Arghir Zarnescu , Elena Akhmatskaya

This paper describes the application of finite-size scaling concepts to domain growth in systems with a non-conserved order parameter. A finite-size scaling ansatz for the time-dependent order parameter distribution function is proposed,…

Condensed Matter · Physics 2009-10-22 Nigel. B. Wilding , Christian Muenkel , Dieter W. Heermann

We present extensive results from 2-dimensional simulations of phase separation kinetics in a model with order-parameter dependent mobility. We find that the time-dependent structure factor exhibits dynamical scaling and the scaling…

Condensed Matter · Physics 2009-10-30 Sanjay Puri , Alan Bray , Joel Lebowitz

This article considers change point testing and estimation for a sequence of high-dimensional data. In the case of testing for a mean shift for high-dimensional independent data, we propose a new test which is based on $U$-statistic in Chen…

Statistics Theory · Mathematics 2021-08-10 Runmin Wang , Changbo Zhu , Stanislav Volgushev , Xiaofeng Shao

In recent years, data dimensionality has increasingly become a concern, leading to many parameter and dimension reduction techniques being proposed in the literature. A parameter-wise co-clustering model, for data modelled via continuous…

Machine Learning · Statistics 2020-10-01 M. P. B. Gallaugher , C. Biernacki , P. D. McNicholas

Roughly half of numerical investigations of the Anderson transition are based on consideration of an associated quasi-1D system and postulation of one-parameter scaling for the minimal Lyapunov exponent. If this algorithm is taken…

Disordered Systems and Neural Networks · Physics 2009-11-11 I. M. Suslov

We study the domain growth of the one-dimensional kinetic Ising model under the competing influence of Glauber dynamics at temperature T and Kawasaki dynamics with a configuration-independent rate. The scaling of the structure factor is…

Statistical Mechanics · Physics 2009-10-31 Zhi-Feng Huang , Bing-Lin Gu , Yun Tang

Comment on R. Planet, S. Santucci, J. Ortin, Phys. Rev. Lett. 102, 094502 (2009) about the rescaling of the data and the data collapse. Reply to be found here.

Statistical Mechanics · Physics 2015-05-19 Gunnar Pruessner

A two-dimensional lattice system of non-interacting electrons in a homogeneous magnetic field with half a flux quantum per plaquette and a random potential is considered. For the large scale behavior a supersymmetric theory with collective…

Mesoscale and Nanoscale Physics · Physics 2009-10-28 K. Ziegler

Recent work has identified simple empirical scaling laws for language models, linking compute budget, dataset size, model size, and autoregressive modeling loss. The validity of these simple power laws across orders of magnitude in model…

Machine Learning · Statistics 2021-09-27 Amélie Chatelain , Amine Djeghri , Daniel Hesslow , Julien Launay , Iacopo Poli
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