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Computer simulations of first-order relaxation processes show that the spatial configurations of the system acquire an invariant shape once the stationary regime is attained. Inspired by them we find that, in any first-order relaxation…

Other Condensed Matter · Physics 2015-06-25 A. Fondado , J. Mira , J. Rivas

We present an empirical study in the geometric task of learning interatomic potentials, which shows equivariance matters even more at larger scales; we show a clear power-law scaling behaviour with respect to data, parameters and compute…

Machine Learning · Computer Science 2026-05-06 Khang Ngo , Siamak Ravanbakhsh

For each type of number, structures that differ by arbitrary scaling factors and are isomorphic to one another are described. The scaling of number values in one structure, relative to the values in another structure, must be compensated…

Rings and Algebras · Mathematics 2013-12-06 Paul Benioff

By the early 1960's advances in statistical physics had established the existence of universality classes for systems with second-order phase transitions and characterized these by critical exponents which are different to the classical…

Statistical Mechanics · Physics 2017-08-23 Ralph Kenna

The law of allometric growth is one of basic rules for understanding urban evolution. The general form of this law is allometric scaling law. However, the deep meaning and underlying rationale of the scaling exponents remain to be brought…

Physics and Society · Physics 2020-04-28 Yanguang Chen

The equation which describes a particle diffusing in a logarithmic potential arises in diverse physical problems such as momentum diffusion of atoms in optical traps, condensation processes, and denaturation of DNA molecules. A detailed…

Statistical Mechanics · Physics 2015-06-03 Ori Hirschberg , David Mukamel , Gunter M. Schütz

The four types of homogeneity -- additive, multiplicative, exponential, and logarithmic -- are generalized as transformations describing how a function $f$ changes under scaling or shifting of its arguments. These generalized homogeneity…

General Mathematics · Mathematics 2026-01-01 Martin Himmel

Size varies. Small things are typically more frequent than large things. The logarithm of frequency often declines linearly with the logarithm of size. That power law relation forms one of the common patterns of nature. Why does the…

Populations and Evolution · Quantitative Biology 2016-11-08 Steven A. Frank

Hierarchies can be modeled by a set of exponential functions, from which we can derive a set of power laws indicative of scaling. The solution to a scaling relation equation is always a power law. The scaling laws are followed by many…

Physics and Society · Physics 2018-12-19 Yanguang Chen , Bin Jiang

We study the finite-size scaling behaviour at the critical point, resulting from the addition of a homogeneous size-dependent perturbation, decaying as an inverse power of the system size. The scaling theory is first formulated in a general…

Statistical Mechanics · Physics 2023-03-06 L. Turban

We show that the natural scaling of measurement for a particular problem defines the most likely probability distribution of observations taken from that measurement scale. Our approach extends the method of maximum entropy to use…

Quantitative Methods · Quantitative Biology 2010-03-02 Steven A. Frank , D. Eric Smith

We advance scale-invariance arguments for systems that are governed (or approximated) by a $q-$Gaussian distribution, i.e., a power law distribution with exponent $Q=1/(1-q); q \in \mathbb{R}$. The ensuing line of reasoning is then compared…

Statistical Mechanics · Physics 2009-11-11 C. Vignat , A. Plastino

Scaling describes how a given quantity $Y$ that characterizes a system varies with its size $P$. For most complex systems it is of the form $Y\sim P^\beta$ with a nontrivial value of the exponent $\beta$, usually determined by regression…

Physics and Society · Physics 2019-10-16 Marc Barthelemy

The success of machine learning has resulted from its structured representation of data. Similar data have close internal representations as compressed codes for classification or emerged labels for clustering. We observe that the frequency…

Machine Learning · Computer Science 2022-04-13 Sungyeop Lee , Junghyo Jo

Scale invariance is a central organizing principle in physics, underlying phenomena that range from critical behaviour in statistical mechanics to transport and chaos in nonlinear dynamical systems. Here we present a unified and physically…

Statistical Mechanics · Physics 2026-02-23 Edson D. Leonel , Diego F. M. Oliveira

Ageing phenomena far from equilibrium naturally present dynamical scaling and in many situations this may generalised to local scale-invariance. Generically, the absence of time-translation-invariance implies that each scaling operator is…

High Energy Physics - Theory · Physics 2026-02-13 Malte Henkel

Scale invariance and the resulting power law behaviours are seen in diverse systems. In this work we consider translation, rotational and scale invariant systems defined on a lattice, such that the variables defining the state at every…

Statistical Mechanics · Physics 2025-05-19 Vaibhav Wasnik

Scaling laws arise and are eulogized across disciplines from natural to social sciences for providing pithy, quantitative, `scale-free', and `universal' power law relationships between two variables. On a log-log plot, the power laws…

Soft Condensed Matter · Physics 2025-07-04 Marc-Antoine Fardin , Mathieu Hautefeuille , Vivek Sharma

We show that in a broad class of processes that show a $1/f^{\alpha}$ spectrum, the power also explicitly depends on the characteristic time scale. Despite an enormous amount of work, this generic behavior remains so far overlooked and…

Statistical Mechanics · Physics 2021-03-23 Avinash Chand Yadav , Naveen Kumar

Large language models with a huge number of parameters, when trained on near internet-sized number of tokens, have been empirically shown to obey neural scaling laws: specifically, their performance behaves predictably as a power law in…

Machine Learning · Computer Science 2022-11-01 Alexander Maloney , Daniel A. Roberts , James Sully
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