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We consider rough paths with jumps. In particular, the analogue of Lyons' extension theorem and rough integration are established in a jump setting, offering a pathwise view on stochastic integration against cadlag processes. A class of…

Probability · Mathematics 2014-12-01 Peter Friz , Atul Shekhar

In this paper, we contribute to the study of the class $(\Sigma)$. In the first part of the paper, we provide new ways to characterize stochastic processes of the above mentioned class and we derive some new properties. For instance, we…

Probability · Mathematics 2018-03-28 Fulgence Eyi Obiang , Octave Moutsinga , Youssef Youssef

We consider anticipative Stratonovich stochastic differential equations driven by some stochastic process lifted to a rough path. Neither adaptedness of initial point and vector fields nor commuting conditions between vector field is…

Probability · Mathematics 2011-11-10 Laure Coutin , Peter Friz , Nicolas Victoir

In this paper, we present a statistical model of spacetime trajectories based on a finite collection of paths organized into a branched manifold. For each configuration of the branched manifold, we define a Shannon entropy. Given the…

Quantum Physics · Physics 2026-03-17 Roukaya Dekhil , Clifford Ellgen , Bruno Klajn

In the article, Besov-Orlicz regularity of sample paths of stochastic processes that are represented by multiple integrals of order $n\in\mathbb{N}$ is treated. We give sufficient conditions for the considered processes to have paths in the…

Probability · Mathematics 2021-11-25 Petr Čoupek , Martin Ondreját

Path integrals are a ubiquitous tool in theoretical physics. However, their use is sometimes hindered by the lack of control on various manipulations -- such as performing a change of the integration path -- one would like to carry out in…

Statistical Mechanics · Physics 2023-04-21 Thibaut Arnoulx de Pirey , Leticia F. Cugliandolo , Vivien Lecomte , Frédéric van Wijland

By using path integrals, the stochastic process associated to the time evolution of the quantum probability density is formally rewritten in terms of a stochastic differential equation, given by Newton's equation of motion with an…

Quantum Physics · Physics 2018-01-04 Marco Patriarca

The paper is devoted to the existence of integral functionals $\int_0^\infty f(X(t))\,{\mathrm{d}t}$ for several classes of processes in $\mathbb{R}$ with $d\ge 3$. Some examples such as Brownian motion, fractional Brownian motion, compound…

Probability · Mathematics 2021-04-02 Yuri Kondratiev , Yuliya Mishura , José L. da Silva

Introduced is the notion of minimality for spectral representations of sum- and max-infinitely divisible processes and it is shown that the minimal spectral representation on a Borel space exists and is unique. This fact is used to show…

Probability · Mathematics 2016-01-18 Zakhar Kabluchko , Stilian Stoev

In this paper we introduce a variant of Burkholder's martingale transform associated with two martingales with respect to different filtrations. Even though the classical martingale techniques cannot be applied, we show that the discussed…

Probability · Mathematics 2015-02-24 Vjekoslav Kovač , Kristina Ana Škreb

A new coupling argument is introduced to establish Driver's integration by parts formula and shift Harnack inequality. Unlike known coupling methods where two marginal processes with different starting points are constructed to move…

Probability · Mathematics 2014-04-01 Feng-Yu Wang

In this work we introduce a theory of stochastic integration for operator-valued integrands with respect to some classes of cylindrical martingale-valued measures in Hilbert spaces. The integral is constructed via the radonification of…

Probability · Mathematics 2021-12-06 A. E. Alvarado-Solano , C. A. Fonseca-Mora

This work shows how exponential concentration inequalities for additive functionals of stochastic processes over a finite time interval can be derived from concentration inequalities for martingales. The approach is entirely probabilistic…

Probability · Mathematics 2020-07-14 Bob Pepin

We construct the basis of a stochastic calculus for so-called Volterra processes, i.e., processes which are defined as the stochastic integral of a time-dependent kernel with respect to a standard Brownian motion. For these processes which…

Probability · Mathematics 2007-05-23 L. Decreusefond

A stochastic calculus is given for processes described by stochastic integrals with respect to fractional Brownian motions and Rosenblatt processes somewhat analogous to the stochastic calculus for It\^{o} processes. These processes for…

Probability · Mathematics 2019-08-02 Petr Čoupek , Tyrone E. Duncan , Bozenna Pasik-Duncan

In the development of stochastic integration and the theory of semimartingales, Markov processes have been a constant source of inspiration. Despite this historical interweaving, it turned out that semimartingales should be considered the…

Probability · Mathematics 2022-11-29 Sebastian Rickelhoff , Alexander Schnurr

The spin coherent state path integral describing the dynamics of a spin-1/2-system in a magnetic field of arbitrary time-dependence is considered. Defining the path integral as the limit of a Wiener regularized expression, the semiclassical…

Quantum Physics · Physics 2008-11-26 Adrian Alscher , Hermann Grabert

Recently, a new approach in the fine analysis of stochastic processes sample paths has been developed to predict the evolution of the local regularity under (pseudo-)differential operators. In this paper, we study the sample paths of…

Probability · Mathematics 2013-08-29 Paul Balança , Erick Herbin

Stochastic symmetries and related invariance properties of finite dimensional SDEs driven by general c\`adl\`ag semimartingales taking values in Lie groups are defined and investigated. In order to enlarge the class of possible symmetries…

Probability · Mathematics 2017-08-08 Sergio Albeverio , Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

We study pathwise approximation of scalar stochastic differential equations at a single point. We provide the exact rate of convergence of the minimal errors that can be achieved by arbitrary numerical methods that are based (in a…

Probability · Mathematics 2007-05-23 Thomas Muller-Gronbach
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