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We investigate piecewise-linear stochastic models as with regards to the probability distribution of functionals of the stochastic processes, a question which occurs frequently in large deviation theory. The functionals that we are looking…

Statistical Mechanics · Physics 2015-06-22 Yaming Chen , Wolfram Just

We review opportunities for stochastic geometric mechanics to incorporate observed data into variational principles, in order to derive data-driven nonlinear dynamical models of effects on the variability of computationally resolvable…

Chaotic Dynamics · Physics 2018-06-28 François Gay-Balmaz , Darryl D. Holm

We prove an It\^o-Wentzell formula for the fractional Brownian motion. As an application we derive an existence and uniqueness result for a class of stochastic differential equations driven by this stochastic process.

Probability · Mathematics 2024-11-19 Luís Maia

In this paper, we consider a kind of fully coupled slow fast motion, in which the slow variable satisfies the non Lipschitz condition. We prove that the stochastic flow of the slow variable exists and moreover, satisfies the large deviation…

Probability · Mathematics 2024-09-20 Mingkun Ye , Zuozheng Zhang

We consider a stochastic flow driven by a finite dimensional Brownian motion. We show that almost every realization of such a flow exhibits strong statistical properties such as the exponential convergence of an initial measure to the…

Probability · Mathematics 2007-05-23 Dmitry Dolgopyat , Vadim Kaloshin , Leonid Koralov

A method of calculation for the variational derivatives for gravitational actions in the pseudo-Riemannian case is proposed as a practical variant of the first order formalism with constraints. The method is then used to derive the metric…

General Relativity and Quantum Cosmology · Physics 2013-10-30 Ahmet Baykal

We show that a pathwise stochastic integral with respect to fractional Brownian motion with an adapted integrand $g$ can have any prescribed distribution, moreover, we give both necessary and sufficient conditions when random variables can…

Probability · Mathematics 2013-03-22 Yuliya Mishura , Georgiy Shevchenko , Esko Valkeila

In this paper, we consider backward stochastic differential equations driven by $G$-Brownian motion (GBSDEs) under quadratic assumptions on coefficients. We prove the existence and uniqueness of solution for such equations. On the one hand,…

Probability · Mathematics 2016-03-18 Ying Hu , Yiqing Lin , Abdoulaye Soumana Hima

We obtain a representation theorem for the generators of BSDEs driven by G-Brownian motions, and then we use the representation theorem to get a converse comparison theorem for G-BSDEs and some equivalent results for nonlinear expectations…

Probability · Mathematics 2013-06-11 Kun Heand , Mingshang Hu

In this paper, we study rough path properties of stochastic integrals of It\^{o}'s type and Stratonovich's type with respect to $G$-Brownian motion. The roughness of $G$-Brownian Motion is estimated and then the pathwise Norris lemma in…

Probability · Mathematics 2016-08-24 Shige Peng , Huilin Zhang

We introduce a variational theory for processes adapted to the multi-dimensional Brownian motion filtration that provides a differential structure allowing to describe infinitesimal evolution of Wiener functionals at very small scales. The…

Probability · Mathematics 2017-12-01 Dorival Leão , Alberto Ohashi , Alexandre B. Simas

In this paper we study the stochastic control problem of partially observed (multi-dimensional) stochastic system driven by both Brownian motions and fractional Brownian motions. In the absence of the powerful tool of Girsanov…

Optimization and Control · Mathematics 2023-08-22 Yueyang Zheng , Yaozhong Hu

In this paper, we establish Girsanov's formula for $G$-Brownian motion. Peng (2007, 2008) constructed $G$-Brownian motion on the space of continuous paths under a sublinear expectation called $G$-expectation; as obtained by Denis et al.…

Probability · Mathematics 2013-02-22 Emi Osuka

This paper deals with the identification of the multivariate fractional Brownian motion, a recently developed extension of the fractional Brownian motion to the multivariate case. This process is a $p$-multivariate self-similar Gaussian…

Statistics Theory · Mathematics 2011-11-16 Pierre-Olivier Amblard , Jean-François Coeurjolly

This paper considers the orthogonal expansion of the fractional Brownian motion relative to the Legendre polynomials. Such an expansion has not only theoretical but also practical interest, since it can be applied to approximate and…

Probability · Mathematics 2026-01-13 Konstantin A. Rybakov

In this paper, we introduce the idea of stochastic integrals with respect to an increasing process in the $G$-framework and extend $G$-It\^o's formula. Moreover, we study the solvability of the scalar valued stochastic differential…

Probability · Mathematics 2015-10-07 Yiqing Lin

We review probabilistic approaches to the Gross-Pitaevskii theory describing interacting dilute systems of particles. The main achievement are large deviations principles for the mean occupation measure of a large system of interacting…

Probability · Mathematics 2007-09-19 Stefan Adams , Wolfgang König

We develop a notion of nonlinear expectation --G-expectation-- generated by a nonlinear heat equation with infinitesimal generator G. We first study multi-dimensional G-normal distributions. With this nonlinear distribution we can introduce…

Probability · Mathematics 2007-05-23 Shige Peng

It is well known that Brownian motion enjoys several distributional invariances such as the scaling property and the time reversal. In this paper, we prove another invariance of Brownian motion that is compatible with the time reversal. The…

Probability · Mathematics 2023-10-20 Yuu Hariya

In this paper, we consider the stochastic optimal control problems under model risk caused by uncertain volatilities. To have a mathematical consistent framework we use the notion of G-expectation and its corresponding G-Brwonian motion…

Optimization and Control · Mathematics 2014-04-18 Zhongyang Sun , Xin Zhang , Junyi Guo