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This paper is devoted to establish an invariance principle where the limit process is a multifractional Gaussian process with a multifractional function which takes its values in $(1/2,1)$. Some properties, such as regularity and local…

Probability · Mathematics 2009-09-29 Serge Cohen , Renaud Marty

A quantum model based on a Euler-Lagrange variational approach is proposed. In analogy with the classical transport, our approach maintain the description of the particle motion in terms of trajectories in a configuration space. Our method…

Mathematical Physics · Physics 2018-07-04 O. Morandi

Weconsider Markov decision processes arising from a Markov model of an underlying natural phenomenon. Such phenomena are usually periodic (e.g. annual) in time, and so the Markov processes modelling them must be time-inhomogeneous, with…

Optimization and Control · Mathematics 2024-09-17 Arash Khojaste , Geoffrey Pritchard , Golbon Zakeri

We obtain an almost sure bound for oscillation rates of empirical distribution functions for stationary causal processes. For short-range dependent processes, the oscillation rate is shown to be optimal in the sense that it is as sharp as…

Probability · Mathematics 2007-05-23 Wei Biao Wu

We extend the recently proposed Time-Dependent Multi-Determinant approach (ref.[1]) to the description of fermionic propagators. The method hinges on equations of motions obtained using variational principles of Dirac type. In particular we…

Nuclear Theory · Physics 2013-12-03 Giovanni Puddu

We consider different types of processes obtained by composing Brownian motion $B(t)$, fractional Brownian motion $B_{H}(t)$ and Cauchy processes $% C(t)$ in different manners. We study also multidimensional iterated processes in…

Probability · Mathematics 2010-08-06 Luisa Beghin , Enzo Orsingher , Lyudmyla Sakhno

This article deals with the numerical resolution of backward stochastic differential equations. Firstly, we consider a rather general case where the filtration is generated by a Brownian motion and a Poisson random measure. We provide a…

Probability · Mathematics 2008-12-18 Emmanuel Gobet , Jean-Philippe Lemor

We start by defining a subordinator by means of the lower-incomplete gamma function. It can be considered as an approximation of the stable subordinator, easier to be handled thank to its finite activity. A tempered version is also…

Probability · Mathematics 2021-06-24 Luisa Beghin , Costantino Ricciuti

The time dependent quantum variational principle is emerging as an important means of studying quantum dynamics, particularly in early universe scenarios. To date all investigations have worked within a Gaussian framework. Here we present…

General Relativity and Quantum Cosmology · Physics 2010-01-06 Gareth J. Cheetham , E. J. Copeland

Bayesian learning using Gaussian processes provides a foundational framework for making decisions in a manner that balances what is known with what could be learned by gathering data. In this dissertation, we develop techniques for…

Machine Learning · Statistics 2022-04-29 Alexander Terenin

In this note, we introduce the notion of $\alpha$-IDT processes which is obtained from a slight and fundamental modification of the IDT property. Several examples of $\alpha$-IDT processes are given and Gaussian processes which are…

Probability · Mathematics 2012-10-17 Antoine Hakassou , Youssef Ouknine

We show how a large family of master equations, describing quantum Brownian motion of a harmonic oscillator with translationally invariant damping, can be derived within a phenomenological approach, based on the assumption that an…

Quantum Physics · Physics 2009-11-13 A. V. Dodonov , S. S. Mizrahi , V. V. Dodonov

We construct a class of one-dimensional diffusion processes on the particles of branching Brownian motion that are symmetric with respect to the limits of random martingale measures. These measures are associated with the extended extremal…

Probability · Mathematics 2018-11-07 Sebastian Andres , Lisa Hartung

The so-called Hadamard fractional Brownian motion, as defined in Beghin et al. (2025) by means of Hadamard fractional operators, is a Gaussian process which shares some properties with standard Brownian motion (such as the one-dimensional…

Probability · Mathematics 2025-07-21 Luisa Beghin , Alessandro De Gregorio , Yuliya Mishura

In the paper we consider models of generalized counting processes time-changed by a general inverse subordinator, we characterize their distributions and present governing equations for them. The equations are given in terms of the…

Probability · Mathematics 2023-12-11 Khrystyna Buchak , Lyudmyla Sakhno

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

Gaussian processes are probabilistic models that are commonly used as functional priors in machine learning. Due to their probabilistic nature, they can be used to capture the prior information on the statistics of noise, smoothness of the…

Computation · Statistics 2024-02-02 Ahmad Farooq , Cristian A. Galvis-Florez , Simo Särkkä

The aim of this paper is to prove an analogue of Baxter's inequality for fractional Brownian motion-type processes with Hurst index less than 1/2. This inequality is concerned with the norm estimate of the difference between finite- and…

Probability · Mathematics 2008-01-17 Akihiko Inoue , Yukio Kasahara , Punam Phartyal

For time-dependent systems the wavefunction depends explicitly on time and it is not a pure state of the Hamiltonian. We construct operators for which the above wavefunction is a pure state. The method is based on the introduction of…

Quantum Physics · Physics 2007-05-23 Victor Tapia

Time-dependent quantum mechanics provides an intuitive picture of particle propagation in external fields. Semiclassical methods link the classical trajectories of particles with their quantum mechanical propagation. Many analytical results…

Mesoscale and Nanoscale Physics · Physics 2008-03-07 Tobias Kramer , Eric J. Heller , Robert E. Parrott