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We revise the problem of the density of states in disordered superconductors. Randomness of local sample characteristics translates to the quenched spatial inhomogeneity of the spectral gap, smearing the BCS coherence peak. We show that…

Superconductivity · Physics 2013-10-16 M. A. Skvortsov , M. V. Feigel'man

In this paper we study an ensemble of random matrices called Elliptic Volatility Model, which arises in finance as models of stock returns. This model consists of a product of independent matrices $X = \Sigma Z $ where $Z$ is a $T$ by $S$…

Probability · Mathematics 2024-02-06 Anna Maltsev , Svetlana Malysheva

We introduce cluster dynamical models of conflicts in which only the largest cluster can be involved in an action. This mimics the situations in which an attack is planned by a central body, and the largest attack force is used. We study…

Physics and Society · Physics 2010-01-19 Bosiljka Tadic , G. J. Rodgers

Stochastic simulations are used to create synthetic one-dimensional telegraph approximation (TA) signals based on turbulent zero crossings, where the interval between crossings is governed by a power law probability distribution with…

Data Analysis, Statistics and Probability · Physics 2022-12-16 Michael Heisel

Power-law probability distributions are widely used to model extreme statistical events in complex systems, with applications to a vast array of natural phenomena ranging from earthquakes to stock market crashes to pandemics. We show that…

Quantum Physics · Physics 2026-04-08 Wai-Keong Mok

We develop an asymptotic theory for extremes in decomposable graphical models by presenting results applicable to a range of extremal dependence types. Specifically, we investigate the weak limit of the distribution of suitably normalised…

Statistics Theory · Mathematics 2023-02-13 Adrian Casey , Ioannis Papastathopoulos

We consider stochastic processes where randomly chosen particles with positive quantities x, y (> 0) interact and exchange the quantities asymmetrically by the rule x' = c{(1-a) x + b y}, y' = d{a x + (1-b) y} (x \ge y), where (0 \le) a, b…

Statistical Mechanics · Physics 2007-05-23 Akihiro Fujihara , Toshiya Ohtsuki , Hiroshi Yamamoto

Starting from the model of continuous time random walk, we focus our interest on random walks in which the probability distributions of the waiting times and jumps have fat tails characterized by power laws with exponent between 0 and 1 for…

Probability · Mathematics 2008-01-03 Rudolf Gorenflo , Entsar A. A. Abdel-Rehim

We study the upper tails for the energy of a randomly charged symmetric and transient random walk. We assume that only charges on the same site interact pairwise. We consider annealed estimates, that is when we average over both randomness,…

Probability · Mathematics 2009-09-29 Amine Asselah

We explore extreme value phenomena in spatial scale-free random graphs in a continuum setting based on a homogeneous Poisson point process in $\mathbb{R}^d$. Vertices carry i.i.d. weights $(W_x)$ and, conditionally on the vertex set and the…

Probability · Mathematics 2026-02-17 Arnaud Rousselle , Ercan Sönmez

The instanton approach to the in-gap fluctuation states is applied to the spectrum of biased bilayer graphene. It is shown that the density of states falls off with energy measured from the band-edge as $\nu(\epsilon)\propto…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 V. V. Mkhitaryan , M. E. Raikh

This paper addresses the statistical properties of time series driven by rational bubbles a la Blanchard and Watson (1982), corresponding to multiplicative maps, whose study has recently be revived recently in physics as a mechanism of…

Statistical Mechanics · Physics 2008-12-02 Thomas Lux , D. Sornette

The extreme value dependence of regularly varying stationary time series can be described by the spectral tail process. Drees, Segers and Warchol [Extremes 18(3): 369--402, 2015] proposed estimators of the marginal distributions of this…

Statistics Theory · Mathematics 2019-07-23 Holger Drees , Miran Knezevic

We extend a generic class of systems which have previously been shown to spontaneously develop scaling (power law) distributions of their elementary degrees of freedom. While the previous systems were linear and exploded exponentially for…

adap-org · Physics 2009-10-28 S. Solomon , M. Levy

We analyze neural scaling laws in a solvable model of last-layer fine-tuning where targets have intrinsic, instance-heterogeneous difficulty. In our Latent Instance Difficulty (LID) model, each input's target variance is governed by a…

Machine Learning · Computer Science 2026-01-08 Noam Levi

Exact analytic calculations in spin-1/2 XY chains, show the presence of long-time tails in the asymptotic dynamics of spatially inhomogeneous excitations. The decay of inhomogeneities, for $t\to \infty $, is given in the form of a power law…

Statistical Mechanics · Physics 2009-11-07 G. O. Berim , S. Berim , G. G. Cabrera

Predicting the occurrence of tail events is of great importance in financial risk management. By employing the method of peak-over-threshold (POT) to identify the financial extremes, we perform a recurrence interval analysis (RIA) on these…

Risk Management · Quantitative Finance 2020-04-09 Wei-Zhen Li , Jin-Rui Zhai , Zhi-Qiang Jiang , Gang-Jin Wang , Wei-Xing Zhou

We consider disordered pinning models, when the return time distribution of the underlying renewal process has a polynomial tail with exponent $\alpha \in (1/2,1)$. This corresponds to a regime where disorder is known to be relevant, i.e.…

Probability · Mathematics 2017-09-01 Francesco Caravenna , Fabio Lucio Toninelli , Niccolo Torri

We consider a directed polymer of length $L$ in a random medium of space dimension $d=1,2,3$. The statistics of low energy excitations as a function of their size $l$ is numerically evaluated. These excitations can be divided into bulk and…

Disordered Systems and Neural Networks · Physics 2007-05-23 Cecile Monthus , Thomas Garel

We study numerically propagation of energy in a one dimensional Ding-Ding lattice, composed of linear oscillators with ellastic collisions. Wave propagation is suppressed by breaking translational symmetry, we consider three way to do this:…

Disordered Systems and Neural Networks · Physics 2020-06-24 A. Pikovsky
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