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Related papers: Finite-size scaling in extreme statistics

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This PhD thesis has the following structure: Chapter 1 - General introduction; Chapter 2 - Preliminaries; Chapter 3 - The Replicated Transfer Matrix; Chapter 4 - Finite Size Corrections On Random Graphs; Chapter 5 - The Random Field Ising…

Disordered Systems and Neural Networks · Physics 2015-02-20 Carlo Lucibello

We study the localization volumes $V$ (participation ratio) of electronic wave functions in the 2d-Anderson model with diagonal disorder. Using a renormalization procedure, we show that at the band edges, i.e. for energies $E\approx \pm 4$,…

Disordered Systems and Neural Networks · Physics 2009-11-10 Stefanie Russ

We propose the use of low bit-depth Sigma-Delta and distributed noise-shaping methods for quantizing the Random Fourier features (RFFs) associated with shift-invariant kernels. We prove that our quantized RFFs -- even in the case of $1$-bit…

Machine Learning · Computer Science 2022-04-14 Jinjie Zhang , Harish Kannan , Alexander Cloninger , Rayan Saab

A system of stochastic differential equations for the velocity and density of a classical self-gravitating matter is investigated by means of the field theoretic renormalization group. The existence of two types of large-scale scaling…

Astrophysics · Physics 2009-11-10 N. V. Antonov

We study the entanglement entropy(EE) of disordered one-dimensional spinless fermions with attractive interactions. With intensive numerical calculation of the EE using the density matrix renormalization group method, we find clear…

Mesoscale and Nanoscale Physics · Physics 2013-03-08 Rui-Lin Chu , An Zhao , Shun-Qing Shen

The long-tailed distribution is a common phenomenon in the real world. Extracted large scale image datasets inevitably demonstrate the long-tailed property and models trained with imbalanced data can obtain high performance for the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-18 Konstantinos Panagiotis Alexandridis , Shan Luo , Anh Nguyen , Jiankang Deng , Stefanos Zafeiriou

Real-world physical signals are continuous and high-dimensional, yet the statistical-mechanics machinery of associative memory operates on discrete Ising spins. We bridge this divide through a multilayer Ising framework that couples a…

Disordered Systems and Neural Networks · Physics 2026-05-15 Andrea Ladiana

We report on the exact treatment of a random-matrix representation of bond percolation model on a square lattice in two dimensions with occupation probability $p$. The percolation problem is mapped onto a random complex matrix composed of…

Statistical Mechanics · Physics 2022-02-14 Azadeh Malekan , Sina Saber , Abbas Ali Saberi

We formulate a renormalisation procedure for IR divergences of tree-level in-in late-time de Sitter correlators. These divergences are due to the infinite volume of spacetime and are analogous to the divergences that appear in AdS dealt…

High Energy Physics - Theory · Physics 2024-06-13 Adam Bzowski , Paul McFadden , Kostas Skenderis

We consider some models in the Kardar-Parisi-Zhang universality class, namely the polynuclear growth model and the totally/partially asymmetric simple exclusion process. For these models, in the limit of large time t, universality of…

Mathematical Physics · Physics 2011-12-22 Patrik L. Ferrari , René Frings

We study the critical behavior of the component sizes for the configuration model when the tail of the degree distribution of a randomly chosen vertex is a regularly-varying function with exponent $\tau-1$, where $\tau\in (3,4)$. The…

Probability · Mathematics 2020-12-22 Souvik Dhara , Remco van der Hofstad , Johan S. H. van Leeuwaarden , Sanchayan Sen

To understand the finite-size-scaling properties of phases transitions in classical and quantum models in the presence of quenched disorder, it has proven to be fruitful to introduce the notion of a finite-size-pseudo-critical point in each…

Disordered Systems and Neural Networks · Physics 2017-01-03 Cecile Monthus

The hyperscaling relation and standard finite-size scaling (FSS) are known to break down above the upper critical dimension due to dangerous irrelevant variables. We establish a coherent formalism for FSS at quantum phase transitions above…

Strongly Correlated Electrons · Physics 2022-10-12 A. Langheld , J. A. Koziol , P. Adelhardt , S. C. Kapfer , K. P. Schmidt

We study extremal statistics and return intervals in stationary long-range correlated sequences for which the underlying probability density function is bounded and uniform. The extremal statistics we consider e.g., maximum relative to…

Statistical Mechanics · Physics 2015-05-13 N. R. Moloney , J. Davidsen

We propose the finite-size scaling of correlation function in a finite system near its critical point. At a distance ${\bf r}$ in the finite system with size $L$, the correlation function can be written as the product of $|{\bf…

Statistical Mechanics · Physics 2018-06-01 Xin Zhang , Gaoke Hu , Yongwen Zhang , Xiaoteng Li , Xiaosong Chen

An analytical realization is suggested for the finite-size scaling algorithm based on the consideration of auxiliary quasi-1D systems. Comparison of the obtained analytical results with the results of numerical calculations indicates that…

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

A class of exact infinitesimal renormalization group transformations is proposed and studied. These transformations are pure changes of variables (i.e., no integration or elimination of some degrees of freedom is required) such that a…

High Energy Physics - Theory · Physics 2017-11-08 Ariel Caticha

In this study, we propose a novel regularization/renormalization scheme that utilizes an auxiliary Feynman parameterization. This approach is employed to align a specified loop diagram with a designated unit of the form $1=\lambda/\lambda$.…

High Energy Physics - Phenomenology · Physics 2025-04-23 Vladimir Sauli

The scaling behaviour of the diffraction intensity near the origin is investigated for (partially) ordered systems, with an emphasis on illustrative, rigorous results. This is an established method to detect and quantify the fluctuation…

Metric Geometry · Mathematics 2021-06-15 Michael Baake , Uwe Grimm

We investigate how extreme loss of data affects the scaling behavior of long-range power-law correlated and anti-correlated signals applying the DFA method. We introduce a segmentation approach to generate surrogate signals by randomly…

Data Analysis, Statistics and Probability · Physics 2010-03-12 Qianli D. Y. Ma , Ronny P. Bartsch , Pedro Bernaola-Galván , Mitsuru Yoneyama , Plamen Ch. Ivanov