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Related papers: Fluctuation theory for level-dependent L\'evy risk…

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Probability density functions (PDFs) of scale-dependent energy fluctuations, $P[\delta E(\ell)]$, are studied in high-resolution direct numerical simulations of Navier-Stokes and incompressible magnetohydrodynamic (MHD) turbulence. MHD…

Fluid Dynamics · Physics 2009-11-13 Mahdi Momeni , Wolf-Christian Müller

We investigate some recursive procedures based on an exact or ``approximate'' Euler scheme with decreasing step in vue to computation of invariant measures of solutions to S.D.E. driven by a L\'evy process. Our results are valid for a large…

Probability · Mathematics 2008-04-02 Fabien Panloup

We consider the problem of valuing a European option written on an asset whose dynamics are described by an exponential L\'evy-type model. In our framework, both the volatility and jump-intensity are allowed to vary stochastically in time…

Pricing of Securities · Quantitative Finance 2013-07-12 Matthew Lorig , Oriol Lozano-Carbassé

A new method is proposed to numerically extract the diffusivity of a (typically nonlinear) diffusion equation from underlying stochastic particle systems. The proposed strategy requires the system to be in local equilibrium and have…

Statistical Mechanics · Physics 2018-05-09 Peter Embacher , Nicolas Dirr , Johannes Zimmer , Celia Reina

We discuss a one-dimensional model of a fluctuating interface with a dynamic exponent $z=1$. The events that occur are adsorption, which is local, and desorption which is non-local and may take place over regions of the order of the system…

Statistical Mechanics · Physics 2016-08-31 Jan de Gier , Bernard Nienhuis , Paul A. Pearce , Vladimir Rittenberg

Large deviation theory (LDT) provides a mathematical framework to quantify the probabilities of rare events in stochastic systems. In this study, we applied LDT to model a chemical reaction system and demonstrated that the fluctuation…

Chemical Physics · Physics 2025-01-22 Tatsuaki Tsuruyama

In the recent paper \cite{Ng5} we have introduced a method of studying the multi-dimensional Kingman convolutions and their associated stochastic processes by embedding them into some multi-dimensional ordinary convolutions which allows to…

Probability · Mathematics 2009-09-09 Thu Nguyen

Long memory processes driven by L\'evy noise with finite second-order moments have been well studied in the literature. They form a very rich class of processes presenting an autocovariance function which decays like a power function. Here,…

Probability · Mathematics 2022-04-20 G. L. Feltes , S. R. C. Lopes

Stochastic thermodynamics is an important development in the direction of finding general thermodynamic principles for non-equilibrium systems. We believe stochastic thermodynamics has the potential to benefit from the measure-theoretic…

Statistical Mechanics · Physics 2023-07-06 Annwesha Dutta , Saikat Sarkar

We develop precise bounds on the growth rates and fluctuation sizes of unbounded solutions of deterministic and stochastic nonlinear Volterra equations perturbed by external forces. The equation is sublinear for large values of the state,…

Classical Analysis and ODEs · Mathematics 2020-11-04 John A. D. Appleby , Denis D. Patterson

In this article, the existence of a unique solution in the variational approach of the stochastic evolution equation $$\dX(t) = F(X(t)) \dt + G(X(t)) \dL(t)$$ driven by a cylindrical L\'evy process $L$ is established. The coefficients $F$…

Probability · Mathematics 2019-12-17 Tomasz Kosmala , Markus Riedle

The fluctuation-dissipation theorem (FDT) is a simple yet powerful consequence of the first-order differential equation governing the dynamics of systems subject simultaneously to dissipative and stochastic forces. The linear learning…

Machine Learning · Computer Science 2021-09-29 Manhyung Han , Jeonghyeok Park , Taewoong Lee , Jung Hoon Han

The meaning of thermodynamic descriptions is found in large-deviations scaling of the fluctuations probabilities. The primary large-deviations rate function is the entropy, which is the basis for both fluctuation theorems and for…

Statistical Mechanics · Physics 2015-05-27 Eric Smith

Extending recent work on stress fluctuations in complex fluids and amorphous solids we describe in general terms the ensemble average $v(\Delta t)$ and the standard deviation $\delta v(\Delta t)$ of the variance $v[\mathbf{x}]$ of time…

Statistical Mechanics · Physics 2020-11-18 G. George , L. Klochko , A. N. Semenov , J. Baschnagel , J. P. Wittmer

A fractional advection-dispersion equation (fADE) has been advocated for heavy-tailed flows where the usual Brownian diffusion models fail. A stochastic differential equation (SDE) driven by a stable L\'{e}vy process gives a forward…

Probability · Mathematics 2019-02-06 Paramita Chakraborty , Xu Guo , Hong Wang

In this paper we consider a finite state time discrete Markov chain that mimics the behaviour of solutions of the stochastic differential equation $dX=-U'(X)dt+\epsilon dL$, where $U$ is a multi-well potential with $n\geq 2$ local minima…

Probability · Mathematics 2015-01-15 Toralf Burghoff , Ilya Pavlyukevich

In the paper we study stochastic convolution appearing in Volterra equation driven by so called L\'evy process. By L\'evy process we mean a process with homogeneous independent increments, continuous in probability and cadlag.

Probability · Mathematics 2007-05-23 Anna Karczewska

We study some SDEs derived from the $q\to 1$ limit of a 2D surface growth model called the $q$-Whittaker process. The fluctuations are proven to exhibit Gaussian characteristics that "come down from infinity": After rescaling and…

Probability · Mathematics 2021-01-12 Yu-Ting Chen

The goal of this paper is to derive a formula for the finite dimensional joint characteristic function (the Fourier transform of the finite dimensional distribution) of the coupled process ${(W_{t},L_{t}^{A}):t\in \lbrack 0,\infty)}$, where…

Probability · Mathematics 2012-06-07 Xi Geng , Zhongmin Qian

We introduce the wavelet scattering spectra which provide non-Gaussian models of time-series having stationary increments. A complex wavelet transform computes signal variations at each scale. Dependencies across scales are captured by the…

Data Analysis, Statistics and Probability · Physics 2023-06-21 Rudy Morel , Gaspar Rochette , Roberto Leonarduzzi , Jean-Philippe Bouchaud , Stéphane Mallat