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We investigate the evolution of barycenters of masses transported by stochastic flows. The state spaces under consideration are smooth affine manifolds with certain convexity structure. Under suitable conditions on the flow and on the…

Probability · Mathematics 2007-05-23 Marc Arnaudon , Xue-Mei Li

We consider a toy model for the study of monitored dynamics in a many-body quantum systems. We study the stochastic Schrodinger equation resulting from the continuous monitoring with a rate $\Gamma$ of a random hermitian operator chosen at…

Statistical Mechanics · Physics 2024-07-02 Federico Gerbino , Pierre Le Doussal , Guido Giachetti , Andrea De Luca

In this article we introduce cylindrical fractional Brownian motions in Banach spaces and develop the related stochastic integration theory. Here a cylindrical fractional Brownian motion is understood in the classical framework of…

Probability · Mathematics 2015-11-19 Elena Issoglio , Markus Riedle

We introduce a stochastic analysis of Grassmann random variables suitable for the stochastic quantization of Euclidean fermionic quantum field theories. Analysis on Grassmann algebras is developed here from the point of view of quantum…

Probability · Mathematics 2022-02-02 Sergio Albeverio , Luigi Borasi , Francesco C. De Vecchi , Massimiliano Gubinelli

We introduce fractional Brownian motion processes (fBm) as an alternative model for the turbulent index of refraction. These processes allow to reconstruct most of the refractive index properties, but they are not differentiable. We…

Optics · Physics 2007-05-23 Dario G. Perez

In this paper we study a parametric class of stochastic processes to model both fast and slow anomalous diffusion. This class, called generalized grey Brownian motion (ggBm), is made up off self-similar with stationary increments processes…

Mathematical Physics · Physics 2009-11-13 Antonio Mura , Gianni Pagnini

We consider three global characteristic times for a one-dimensional Brownian motion $x(\tau)$ in the interval $\tau\in [0,t]$: the occupation time $t_{\rm o}$ denoting the cumulative time where $x(\tau)>0$, the time $t_{\rm m}$ at which the…

Statistical Mechanics · Physics 2025-05-01 Alexander K. Hartmann , Satya N. Majumdar

We introduce a new Gaussian process, a generalization of both fractional and subfractional Brownian motions, which could serve as a good model for a larger class of natural phenomena. We study its main stochastic properties and some…

Probability · Mathematics 2017-04-10 Mounir Zili

The problem of Brownian motion in a periodic potential, under the influence of external forcing, which is either random or periodic in time, is studied in this paper. Multiscale techniques are used to derive general formulae for the steady…

Statistical Mechanics · Physics 2007-05-23 G. A. Pavliotis

Given a large, high-dimensional sample from a spiked population, the top sample covariance eigenvalue is known to exhibit a phase transition. We show that the largest eigenvalues have asymptotic distributions near the phase transition in…

Probability · Mathematics 2013-07-24 Alex Bloemendal , Bálint Virág

The Arcsine laws of Brownian motion are a collection of results describing three different statistical quantities of one-dimensional Brownian motion: the time at which the process reaches its maximum position, the total time the process…

Statistical Mechanics · Physics 2023-08-03 Toby Kay , Luca Giuggioli

We consider a stochastic process $Y$ defined by an integral in quadratic mean of a deterministic function $f$ with respect to a Gaussian process $X$, which need not have stationary increments. For a class of Gaussian processes $X$, it is…

Probability · Mathematics 2015-06-01 Rimas Norvaiša

In this paper, a study of random times on filtered probability spaces is undertaken. The main message is that, as long as distributional properties of optional processes up to the random time are involved, there is no loss of generality in…

Probability · Mathematics 2015-03-17 Constantinos Kardaras

After some normalization, the logarithms of the ordered singular values of Brownian motions on $GL(N,\mathbb F)$ with $\mathbb F=\mathbb R, \mathbb C$ form Weyl-group invariant Heckman-Opdam processes on $\mathbb R^N$ of type $A_{N-1}$. We…

Probability · Mathematics 2025-12-12 Martin Auer , Michael Voit

We study a (relativistic) Wiener process on a complexified (pseudo-)Riemannian manifold. Using Nelson's stochastic quantization procedure, we derive three equivalent descriptions for this problem. If the process has a purely real quadratic…

Mathematical Physics · Physics 2022-05-17 Folkert Kuipers

Operator fractional Brownian fields (OFBFs) are Gaussian, stationary-increment vector random fields that satisfy the operator self-similarity relation {X(c^{E}t)}_{t in R^m} L= {c^{H}X(t)}_{t in R^m}. We establish a general harmonizable…

Probability · Mathematics 2014-05-26 Changryong Baek , Gustavo Didier , Vladas Pipiras

We study extreme-value statistics of Brownian trajectories in one dimension. We define the maximum as the largest position to date and compare maxima of two particles undergoing independent Brownian motion. We focus on the probability P(t)…

Statistical Mechanics · Physics 2014-07-29 E. Ben-Naim , P. L. Krapivsky

We give a stochastic proof of the finite approximability of a class of Schr\"odinger operators over a local field, thereby completing a program of establishing in a non-Archimedean setting corresponding results and methods from the…

Mathematical Physics · Physics 2017-06-28 Erik M. Bakken , Trond Digernes , David Weisbart

The stochastic rotational invariance of an integration by parts formula inspired by the Bismut approach to Malliavin calculus is proved in the framework of the Lie symmetry theory of stochastic differential equations. The non-trivial effect…

Probability · Mathematics 2025-06-16 Susanna Dehò , Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

We consider fluctuations of the largest eigenvalues of the random matrix model $A+UBU^{*}$ where $A$ and $B$ are $N \times N$ deterministic Hermitian (or symmetric) matrices and $U$ is a Haar-distributed unitary (or orthogonal) matrix. We…

Probability · Mathematics 2023-03-08 Hong Chang Ji , Jaewhi Park
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