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We construct a stochastic process, called the Liouville Brownian motion, which is the Brownian motion associated to the metric $e^{\gamma X(z)}\,dz^2$, $\gamma<\gamma_c=2$ and $X$ is a Gaussian Free Field. Such a process is conjectured to…

Probability · Mathematics 2016-09-05 Christophe Garban , Rémi Rhodes , Vincent Vargas

The process $(G_t)_{t\in[0,T]}$ is referred to as a fractional Gaussian process if the first-order partial derivative of the difference between its covariance function and that of the fractional Brownian motion $(B^H_t)_{t\in[0,T ]}$ is a…

Probability · Mathematics 2023-09-20 Yong Chen , Ying Li

Extensions of the fractional Brownian fields are constructed over a complete Riemannian manifold. This construction is carried out for the full range of the Hurst parameter $\alpha\in(0,1)$. In particular, we establish existence,…

Probability · Mathematics 2013-02-19 Zachary Gelbaum

Starting with a Brownian motion, we define and study a novel diffusion process by combining stickiness and oscillation properties. The associated stochastic differential equation, resolvent and semigroup are provided. Also the trivariate…

Probability · Mathematics 2023-02-08 Wajdi Touhami

Brownian motions on a metric graph are defined, their Feller property is proved, and their generators are characterized. This yields a version of Feller's theorem for metric graphs.

Probability · Mathematics 2010-12-07 Vadim Kostrykin , Jürgen Potthoff , Robert Schrader

With the rich dynamics studies of single-state processes, the two-state processes attract more and more interests of people, since they are widely observed in complex system and have effective applications in diverse fields, say, foraging…

Classical Physics · Physics 2019-07-31 Xudong Wang , Yao Chen , Weihua Deng

The main goal of this paper is to provide a fractional stochastic differential equation modelling the physical phenomena governed by the Langevin equation in 1-dimension. A generalized equation leaning on the fractional Brownian motion…

Mathematical Physics · Physics 2008-07-03 Lounis Tewfik , Saïd Bouabdellah

We consider a model of active Brownian particles with velocity-alignment in two spatial dimensions with passive and active fluctuations. Hereby, active fluctuations refers to purely non-equilibrium stochastic forces correlated with the…

Statistical Mechanics · Physics 2016-05-02 Robert Grossmann , Lutz Schimansky-Geier , Pawel Romanczuk

A simple variogram model with two parameters is presented that includes the power variogram for the fractional Brownian motion, a modified De Wijsian model, the generalized Cauchy model and the multiquadrics model. One parameter controls…

Methodology · Statistics 2014-12-08 Martin Schlather

We find an explicit expression for the cross-covariance between stochastic integral processes with respect to a $d$-dimensional fractional Brownian motion (fBm) $B_t$ with Hurst parameter $H>1/2$, where the integrands are vector fields…

Probability · Mathematics 2016-12-16 Yohaï Maayan , Eddy Mayer-Wolf

We investigate the motion of an inert (massive) particle being impinged from below by a particle performing (reflected) Brownian motion. The velocity of the inert particle increases in proportion to the local time of collisions and…

Probability · Mathematics 2017-02-24 Sayan Banerjee , Krzysztof Burdzy , Mauricio Duarte

We consider a problem of statistical estimation of an unknown drift parameter for a stochastic differential equation driven by fractional Brownian motion. Two estimators based on discrete observations of solution to the stochastic…

Probability · Mathematics 2013-09-26 Yuliya Mishura , Kostiantyn Ral'chenko , Oleg Seleznev , Georgiy Shevchenko

We construct and study branching fractional Brownian motion with Hurst parameter $H\in(1/2,1)$. The construction relies on a generalization of the discrete approximation of fractional Brownian motion (Hammond and Sheffield, Probability…

Probability · Mathematics 2024-04-24 Adrián González Casanova , Jan Lukas Igelbrink

The purpose of the article is twofold. Firstly, we review some recent results on the maximum likelihood estimation in the regression model of the form $X_t = \theta G(t) + B_t$, where $B$ is a Gaussian process, $G(t)$ is a known function,…

Probability · Mathematics 2018-12-27 Yuliya Mishura , Kostiantyn Ralchenko , Sergiy Shklyar

In a two-state free probability space $(A, \phi, \psi)$, we define an algebraic two-state free Brownian motion to be a process with two-state freely independent increments whose two-state free cumulant generating function is quadratic. Note…

Operator Algebras · Mathematics 2011-06-14 Michael Anshelevich

We review several results related to the problem of a quantum particle in a random environment. In an introductory part, we recall how several functionals of the Brownian motion arise in the study of electronic transport in weakly…

Disordered Systems and Neural Networks · Physics 2007-05-23 Alain Comtet , Jean Desbois , Christophe Texier

We study the functional link between the Hurst parameter and the Normalized Total Wavelet Entropy when analyzing fractional Brownian motion (fBm) time series--these series are synthetically generated. Both quantifiers are mainly used to…

Data Analysis, Statistics and Probability · Physics 2009-11-11 Dario G. Perez , Luciano Zunino , Mario Garavaglia , Osvaldo A. Rosso

The sub-fractional Brownian motion (sfBm) is a stochastic process, characterized by non-stationarity in their increments and long-range dependency, considered as an intermediate step between the standard Brownian motion (Bm) and the…

Mathematical Finance · Quantitative Finance 2021-04-09 Axel A. Araneda , Nils Bertschinger

We study the motion of an elastic object driven in a disordered environment in presence of both dissipation and inertia. We consider random forces with the statistics of random walks and reduce the problem to a single degree of freedom. It…

Disordered Systems and Neural Networks · Physics 2013-08-22 Pierre Le Doussal , Aleksandra Petkovic , Kay Jörg Wiese

The multiple disorder problem seeks to determine a sequence of stopping times which are as close as possible to the unknown times of disorders at which the observation process changes its probability characteristics. We derive closed form…

Applications · Statistics 2010-11-02 Pavel V. Gapeev