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Motivated by the papers of Mladenovc and Piterbarg (2006), Krajka (2011) and Pereira and Tan (2017), we study the limit properties for the maxima from nonstationary random fields subject to missing observations and obtain the weakly…

Probability · Mathematics 2023-06-27 Shengchao Zheng , Zhongquan Tan

The scaling invariance for chaotic orbits near a transition from unlimited to limited diffusion in a dissipative standard mapping is explained via the analytical solution of the diffusion equation. It gives the probability of observing a…

Chaotic Dynamics · Physics 2020-12-02 Edson D. Leonel , Celia Mayumi Kuwana , Makoto Yoshida , Juliano Antonio de Oliveira

We study the influence of short-range electron-electron interactions on scaling behavior near the integer quantum Hall plateau transitions. Short-range interactions are known to be irrelevant at the renormalization group fixed point which…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 Ziqiang Wang , Matthew P. A. Fisher , S. M. Girvin , J. T. Chalker

With large-scale Monte Carlo simulations, we investigate the nonsteady relaxation at the dynamic depinning transition in the two-dimensional Gaussian random-field Ising model. The dynamic scaling behavior is carefully analyzed, and the…

Statistical Mechanics · Physics 2023-06-21 Xiaohui Qian , Gaotian Yu , Nengji Zhou

We present a scaling theory for the effect of thermal fluctuations on the characteristics of the depinning transition, and also in the closely related directed percolation model. Thermal effects act as a sort of external field that produces…

Statistical Mechanics · Physics 2017-04-07 E. A. Jagla

We study a zero-temperature phase transition in the random field Ising model on scale-free networks with the degree exponent $\gamma$. Using an analytic mean-field theory, we find that the spins are always in the ordered phase for…

Statistical Mechanics · Physics 2007-05-23 Sang Hoon Lee , Hawoong Jeong , Jae Dong Noh

Scattering transform is a well known powerful tool for quantisation of field theories in (1+1) dimensions. Conventionally only those models whose classical counterparts admit a Lax pair (origin of which is always mysterious) have been…

High Energy Physics - Theory · Physics 2007-05-23 Gautam Bhattacharya

We consider quantum and classical first-order transitions, at equilibrium and under out-of-equilibrium conditions, mainly focusing on quench and slow quasi-adiabatic protocols. For these phenomena, we review the finite-size scaling theory…

Statistical Mechanics · Physics 2025-07-01 Andrea Pelissetto , Ettore Vicari

We show that the variation of the ground state entanglement in linear, higher spatial derivatives field theories at zero-temperature have signatures of phase transition. Around the critical point, when the dispersion relation changes from…

High Energy Physics - Theory · Physics 2015-06-12 Suman Ghosh , S. Shankaranarayanan

The risk of occurrence of atypical phenomena is a cross-cutting concern in several areas, such as engineering, climatology, finance, actuarial, among others. Extreme value theory is the natural tool to approach this theme. Many of these…

Statistics Theory · Mathematics 2020-07-09 Marta Ferreira , Ana Paula Martins , Helena Ferreira

Certain frustrated systems, including spin ice and dimer models, exhibit a Coulomb phase at low temperatures, with power-law correlations and fractionalized monopole excitations. Transitions out of this phase, at which the effective gauge…

Statistical Mechanics · Physics 2012-08-09 Stephen Powell

Using the hierarchical approximation, we discuss the cut-off dependence of the renormalized quantities of a scalar field theory. The naturalness problem and questions related to triviality bounds are briefly discussed. We discuss unphysical…

High Energy Physics - Theory · Physics 2007-05-23 Y. Meurice , S. Niermann , G. Ordaz

An isotropic passive scalar field $T$ advected by a rapidly-varying velocity field is studied. The tail of the probability distribution $P(\theta,r)$ for the difference $\theta$ in $T$ across an inertial-range distance $r$ is found to be…

chao-dyn · Physics 2009-10-28 Robert H. Kraichnan

Random fields are commonly used for modeling of spatially (or timely) dependent stochastic processes. In this study, we provide a characterization of the intrinsic complexity of a random field in terms of its second order statistics, e.g.,…

Statistics Theory · Mathematics 2018-05-07 Jennifer Bryson , Hongkai Zhao , Yimin Zhong

Physical systems with many degrees of freedom can often be understood in terms of transitions between a small number of metastable states. For time-homogeneous systems with short-term memory these transitions are fully characterized by a…

Molecular Networks · Quantitative Biology 2015-06-03 Nils B. Becker , Pieter Rein ten Wolde

We investigate scaling limits of trees built by uniform attachment with freezing, which is a variant of the classical model of random recursive trees introduced in a companion paper. Here vertices are allowed to freeze, and arriving…

Probability · Mathematics 2024-04-09 Étienne Bellin , Arthur Blanc-Renaudie , Emmanuel Kammerer , Igor Kortchemski

The critical point of a topological phase transition is described by a conformal field theory, where finite-size corrections to energy are uniquely related to its central charge. We investigate the finite-size scaling away from criticality…

Statistical Mechanics · Physics 2016-01-18 Tobias Gulden , Michael Janas , Yuting Wang , Alex Kamenev

Relations between critical exponents, or scaling laws, at both continuous and discontinuous quantum phase transitions are derived and discussed. In general there are multiple dynamical exponents at these transitions, which complicates the…

Statistical Mechanics · Physics 2015-09-03 T. R. Kirkpatrick , D. Belitz

Scalarization is a mechanism that endows strongly self-gravitating bodies, such as neutron stars and black holes, with a scalar-field configuration. It resembles a phase transition in that the scalar configuration appears only when a…

General Relativity and Quantum Cosmology · Physics 2024-09-11 Daniela D. Doneva , Fethi M. Ramazanoğlu , Hector O. Silva , Thomas P. Sotiriou , Stoytcho S. Yazadjiev

Concept drift, i.e., the change of the data generating distribution, can render machine learning models inaccurate. Several works address the phenomenon of concept drift in the streaming context usually assuming that consecutive data points…

Machine Learning · Computer Science 2023-12-19 Fabian Hinder , Valerie Vaquet , Barbara Hammer
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