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We study the anomalous transport in systems of random walks (RW's) on comb-like lattices with fractal sidebranches, showing subdiffusion, and in a system of Brownian particles driven by a random shear along the x-direction, showing a…

Statistical Mechanics · Physics 2022-06-15 Fabio Cecconi , Giulio Costantini , Alessandro Taloni , Angelo Vulpiani

A theoretical framework is developed to describe the transformation that distributes probability density functions uniformly over space. In one dimension, the cumulative distribution can be used, but does not generalize to higher…

Neural and Evolutionary Computing · Computer Science 2016-09-08 Eric Kee

This letter presents a new approach using the cosmic peculiar velocity field to characterize the morphology and size of large scale structures in the local Universe. The algorithm developed uses the three-dimensional peculiar velocity field…

Cosmology and Nongalactic Astrophysics · Physics 2019-07-31 A. Dupuy , H. M. Courtois , F. Dupont , F. Denis , R. Graziani , Y. Copin , D. Pomarede , N. Libeskind , E. Carlesi , B. Tully , D. Guinet

We study a driven zero range process which models a closed system of attractive particles that hop with site-dependent rates and whose steady state shows a condensation transition with increasing density. We characterise the dynamical…

Statistical Mechanics · Physics 2009-11-10 Kavita Jain , Mustansir Barma

We are concerned with zeros of random power series with coefficients being a stationary, centered, complex Gaussian process. We show that the expected number of zeros in every smooth domain in the disk of convergence is less than that of…

Probability · Mathematics 2021-06-08 Kohei Noda , Tomoyuki Shirai

We analytically study a system of spinless fermions driven at the boundary with an oscillating chemical potential. Various transport regimes can be observed: at zero driving frequency the particle current through the system is independent…

Quantum Physics · Physics 2011-11-22 Marko Znidaric , Bojan Zunkovic , Tomaz Prosen

Consider a centered smooth Gaussian random field $\{X(t), t\in T \}$ with a general (nonconstant) variance function. In this work, we demonstrate that as $u \to \infty$, the excursion probability $\mathbb{P}\{\sup_{t\in T} X(t) \geq u\}$…

Probability · Mathematics 2023-09-12 Dan Cheng

We use simple equations in order to compare the basins of attraction on the complex plane, corresponding to a large collection of numerical methods, of several order. Two cases are considered, regarding the total number of the roots, which…

Numerical Analysis · Mathematics 2024-12-20 Euaggelos E. Zotos , Md Sanam Suraj , Amit Mittal , Rajiv Aggarwal

Proper modeling of complex systems requires innovative mathematical tools. In this sense, we sought to use deformed or fractal derivatives for studying the dynamics of systems, particularly those, such as granular gases, in which the…

Statistical Mechanics · Physics 2024-06-27 José Weberszpil , Cresus F. de L. Godinho , Ion Vasile Vancea

In this paper we consider the distribution of the zeros of a real random Bargmann-Fock function of one or more variables. For these random functions we prove estimates for two types of families of events, both of which are large deviations…

Complex Variables · Mathematics 2008-07-04 Scott Zrebiec

Branching random flights are key to describing the evolution of many physical and biological systems, ranging from neutron multiplication to gene mutations. When their paths evolve in bounded regions, we establish a relation between the…

Statistical Mechanics · Physics 2012-12-17 Andrea Zoia , Eric Dumonteil , Alain Mazzolo

We consider Gaussian signals, i.e. random functions $u(t)$ ($t/L \in [0,1]$) with independent Gaussian Fourier modes of variance $\sim 1/q^{\alpha}$, and compute their statistical properties in small windows $[x, x+\delta]$. We determine…

Disordered Systems and Neural Networks · Physics 2010-09-16 Alberto Rosso , Raoul Santachiara , Werner Krauth

Transport of scalar fields in compressible flow is investigated. The effective equations governing the transport at scales large compared to those of the advecting flow are derived by using multi-scale techniques. Ballistic transport…

chao-dyn · Physics 2009-10-28 M. Vergassola , M. Avellaneda

We suggest a governing equation which describes the process of polymer chain translocation through a narrow pore and reconciles the seemingly contradictory features of such dynamics: (i) a Gaussian probability distribution of the…

Soft Condensed Matter · Physics 2011-02-15 Johan L. A. Dubbeldam , V. G. Rostiashvili , A. Milchev , T. A. Vilgis

Inverse problems in physical or biological sciences often involve recovering an unknown parameter that is random. The sought-after quantity is a probability distribution of the unknown parameter, that produces data that aligns with…

Machine Learning · Statistics 2024-10-02 Qin Li , Maria Oprea , Li Wang , Yunan Yang

We study the probability that a real stationary Gaussian process has at least $\eta T$ zeros in $[0,T]$ (overcrowding), or at most this number (undercrowding). We show that if the spectral measure of the process is supported on $\pm[B,A]$,…

Probability · Mathematics 2023-07-11 Naomi Feldheim , Ohad Feldheim , Lakshmi Priya

The extraction of natural gas from the earth has been shown to be governed by differential equations concerning flow through a porous material. Recently, models such as fractional differential equations have been developed to model this…

Applications · Statistics 2017-09-27 Joshua Whitlinger , Edward L Boone , Ryad Ghanam

Suppose that a $d$-dimensional domain is filled with a gas of (in general, interacting) diffusive particles with density $n_0$. A particle is absorbed whenever it reaches the domain boundary. Employing macroscopic fluctuation theory, we…

Statistical Mechanics · Physics 2016-01-27 Tal Agranov , Baruch Meerson , Arkady Vilenkin

This paper considers the problem of regression over distributions, which is becoming increasingly important in machine learning. Existing approaches often ignore the geometry of the probability space or are computationally expensive. To…

Machine Learning · Computer Science 2025-10-31 Maksim Maslov , Alexander Kugaevskikh , Matthew Ivanov

We present several refinements on the fluctuations of sequences of random vectors (with values in the Euclidean space $\mathbb{R}^d$) which converge after normalization to a multidimensional Gaussian distribution. More precisely we refine…

Probability · Mathematics 2022-03-04 Pierre-Loïc Méliot , Ashkan Nikeghbali
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