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Related papers: Finite-size scaling in extreme statistics

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We study exact renormalisation group equations for the 3d Ising universality class. At the Wilson-Fisher fixed point, symmetric and antisymmetric correction-to-scaling exponents are computed with high accuracy for an optimised cutoff to…

High Energy Physics - Theory · Physics 2009-11-10 Daniel F. Litim , Lautaro Vergara

Finite-size scaling above the upper critical dimension is a long-standing puzzle in the field of Statistical Physics. Even for pure systems various scaling theories have been suggested, partially corroborated by numerical simulations. In…

Statistical Mechanics · Physics 2023-10-30 Nikolaos G. Fytas , Victor Martin-Mayor , Giorgio Parisi , Marco Picco , Nicolas Sourlas

We show numerically that correlation length at the critical point in the five-dimensional Ising model varies with system size L as L^{5/4}, rather than proportional to L as in standard finite size scaling (FSS) theory. Our results confirm a…

Disordered Systems and Neural Networks · Physics 2009-11-10 Jeff L. Jones , A. P. Young

Diffusion on a T fractal lattice under the influence of topological biasing fields is studied by finite size scaling methods. This allows to avoid proliferation and singularities which would arise in a renormalization group approach on…

Condensed Matter · Physics 2015-06-25 G. Sartoni , A. L. Stella

We propose a treatment of the subleading corrections to finite-size scaling that preserves the notion of data collapse. This approach is used to extend and improve the usual Binder cumulant analysis. As a demonstration, we present results…

Statistical Mechanics · Physics 2007-05-23 K. S. D. Beach , Ling Wang , Anders W. Sandvik

Multifractal Detrended Fluctuation Analysis (MFDFA) has emerged as a standard tool for characterizing scale invariance in complex systems, yet its application to discrete spin models is frequently marred by reports of ``spurious…

Statistical Mechanics · Physics 2026-04-01 Sebastian Jaroszewicz , Nahuel Mendez , Maria P. Beccar-Varela , Maria Cristina Mariani

We test the universal finite-size scaling of the cluster mass order parameter in two-dimensional (2D) isotropic and directed continuum percolation models below the percolation threshold by computer simulations. We found that the simulation…

Condensed Matter · Physics 2015-06-25 Van Lien Nguyen , Enrique Canessa

In the classical theorems of extreme value theory the limits of suitably rescaled maxima of sequences of independent, identically distributed random variables are studied. So far, only affine rescalings have been considered. We show,…

Mathematical Physics · Physics 2015-05-30 Iván Calvo , Juan C. Cuchí , José G. Esteve , Fernando Falceto

We analytically derive, in the context of the replica formalism, the first finite size corrections to the average optimal cost in the random assignment problem for a quite generic distribution law for the costs. We show that, when moving…

Disordered Systems and Neural Networks · Physics 2017-05-18 Sergio Caracciolo , Matteo P. D'Achille , Enrico M. Malatesta , Gabriele Sicuro

Scalar field theories with $\mathbb{Z}_{2}$-symmetry are the traditional playground of critical phenomena. In this work these models are studied using functional renormalization group (FRG) equations at order $\partial^2$ of the derivative…

High Energy Physics - Theory · Physics 2018-08-01 N. Defenu , A. Codello

Above the upper critical dimension, the breakdown of hyperscaling is associated with dangerous irrelevant variables in the renormalization group formalism at least for systems with periodic boundary conditions. While these have been…

Statistical Mechanics · Physics 2014-02-10 Bertrand Berche , Ralph Kenna , Jean-Charles Walter

Using single cluster flip Monte Carlo simulations we accurately determine new finite size scaling functions which are expressed only in terms the variable $x = \xi_L / L$, where $\xi_L$ is the correlation length in a finite system of size…

Condensed Matter · Physics 2009-10-28 Jae-Kwon Kim , Adauto J. F. de Souza\cite{addr} , D. P. Landau

The scaling form of the whole distribution P(D) of the random diffusion coefficient D(x) in a model of classically diffusing particles is investigated. The renormalization group approach above the lower critical dimension d=0 is applied to…

Condensed Matter · Physics 2009-10-22 Yan-Chr Tsai , Yonathan Shapir

Noise-shaping quantization techniques are widely used for converting bandlimited signals from the analog to the digital domain. They work by ``shaping" the quantization noise so that it falls close to the reconstruction operator's null…

Information Theory · Computer Science 2026-05-21 Rohan Joy , Felix Krahmer , Alessandro Lupoli , Radha Ramakrishnan

Diffusion models are widely used for generative tasks across domains. Given a pre-trained diffusion model, it is often desirable to fine-tune it further either to correct for errors in learning or to align with downstream applications.…

In statistical mechanics, evaluating finite-size macroscopic fluctuations typically relies on Edgeworth expansions. However, these perturbative methods append additive polynomial corrections that inevitably break down in the large deviation…

Information Theory · Computer Science 2026-04-15 Hiroki Suyari

A finite size scaling theory for the partition function zeros and thermodynamic functions of O(N) phi^4-theory in four dimensions is derived from renormalization group methods. The leading scaling behaviour is mean-field like with…

High Energy Physics - Lattice · Physics 2016-09-01 R. Kenna

We study the 3d Ising universality class using the functional renormalisation group. With the help of background fields and a derivative expansion up to fourth order we compute the leading index, the subleading symmetric and anti-symmetric…

High Energy Physics - Theory · Physics 2011-04-22 Daniel F. Litim , Dario Zappalá

We carry out a finite size scaling analysis of the jamming transition in frictionless bi-disperse soft core disks in two dimensions. We consider two different jamming protocols: (i) quench from random initial positions, and (ii) quasistatic…

Soft Condensed Matter · Physics 2015-05-20 Daniel Vagberg , Daniel Valdez-Balderas , M. A. Moore , Peter Olsson , S. Teitel

We consider a statistical inverse learning problem, where we observe the image of a function $f$ through a linear operator $A$ at i.i.d. random design points $X_i$, superposed with an additive noise. The distribution of the design points is…

Machine Learning · Statistics 2016-04-15 Gilles Blanchard , Nicole Mücke