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Motivated by the modeling of the temporal structure of the velocity field in a highly turbulent flow, we propose and study a linear stochastic differential equation that involves the ingredients of a Ornstein-Uhlenbeck process, supplemented…

Fluid Dynamics · Physics 2017-09-26 Laurent Chevillard

We show that nonequilibrium dynamics can play a constructive role in unsupervised machine learning by inducing the spontaneous emergence of latent-state cycles. We introduce a model in which visible and hidden variables interact through two…

Statistical Mechanics · Physics 2026-05-05 Marco Baiesi , Alberto Rosso

We introduce the elliptical Ornstein-Uhlenbeck (OU) process, which is a generalisation of the well-known univariate OU process to bivariate time series. This process maps out elliptical stochastic oscillations over time in the complex…

Methodology · Statistics 2021-12-08 Adam M. Sykulski , Sofia C. Olhede , Hanna M. Sykulska-Lawrence

We model the time evolution of single win odds in Japanese horse racing as a stochastic process, deriving an Ornstein--Uhlenbeck process by analyzing the probability dynamics of vote shares and the empirical time series of odds movements.…

Physics and Society · Physics 2025-05-22 Tomoya Sugawara , Shintaro Mori

Exponential L\'evy processes have been used for modelling financial derivatives because of their ability to exhibit many empirical features of markets. Using their multidimensional analogue, a general analytic pricing formula is obtained,…

Pricing of Securities · Quantitative Finance 2013-09-13 D. J. Manuge

Ornstein-Uhlenbeck process of bounded variation is introduced as a solution of an analogue of the Langevin equation with an integrated telegraph process replacing a Brownian motion. There is an interval $I$ such that the process starting…

Probability · Mathematics 2020-07-17 Nikita Ratanov

Many physical and biological systems rely on the progression of material through multiple independent stages. In viral replication, for example, virions enter a cell to undergo a complex process comprising several disparate stages before…

Molecular Networks · Quantitative Biology 2024-04-03 Alexander P Browning , Adrianne L Jenner , Ruth E Baker , Philip K Maini

Diffusion based generative models have achieved unprecedented fidelity in synthesizing high dimensional data, yet the theoretical mechanisms governing multimodal generation remain poorly understood. Here, we present a theoretical framework…

Machine Learning · Computer Science 2026-02-10 Emil Albrychiewicz , Andrés Franco Valiente , Li-Ching Chen

Multivariate subordinated L\'evy processes are widely employed in finance for modeling multivariate asset returns. We propose to exploit non-linear dependence among financial assets through multivariate cumulants of these processes, for…

Statistics Theory · Mathematics 2020-04-09 Elvira Di Nardo , Marina Marena , Patrizia Semeraro

In this study we consider the pricing of energy derivatives when the evolution of spot prices follows a tempered stable or a CGMY driven Ornstein- Uhlenbeck process. To this end, we first calculate the characteristic function of the…

Computational Finance · Quantitative Finance 2021-03-25 Piergiacomo Sabino

We consider the inelastic Maxwell model, which consists of a collection of particles that are characterized by only their velocities, and evolving through binary collisions and external driving. At any instant, a particle is equally likely…

Statistical Mechanics · Physics 2015-07-23 V. V. Prasad , Sanjib Sabhapandit , Abhishek Dhar

This article deals with adaptive nonparametric estimation for L\'evy processes observed at low frequency. For general linear functionals of the L\'evy measure, we construct kernel estimators, provide upper risk bounds and derive rates of…

Statistics Theory · Mathematics 2014-07-15 Johanna Kappus

A version of the saddle point method is developed, which allows one to describe exactly the asymptotic behavior of distribution densities of Levy driven stochastic integrals with deterministic kernels. Exact asymptotic behavior is…

Probability · Mathematics 2011-02-08 Victoria P. Knopova , Alexey M. Kulik

Uncertainty propagation in high-dimensional nonlinear dynamic structural systems is pivotal in state-of-the-art performance-based design and risk assessment, where uncertainties from both excitations and structures, i.e., the aleatoric…

Machine Learning · Computer Science 2026-04-03 Manisha Sapkota , Min Li , Bowei Li

Consciousness is supported by complex patterns of brain activity which are indicative of irreversible non-equilibrium dynamics. While the framework of stochastic thermodynamics has facilitated the understanding of physical systems of this…

Neurons and Cognition · Quantitative Biology 2023-03-01 Matthieu Gilson , Enzo Tagliazucchi , Rodrigo Cofre

Let $\mathbb{R}^N_+= [0,\infty)^N$. We here consider a class of random fields $(X_t)_{t\in \mathbb{R}^N_+}$ which are known as Multiparameter L\'evy processes. Related multiparameter semigroups of operators and their generators are…

Probability · Mathematics 2023-05-31 Francesco Iafrate , Costantino Ricciuti

In stochastic population dynamics, stochastic wandering can produce transition to an absorbing state. In particular, under Allee effects, low densities amplify the possibility of population collapse. We investigate this in an…

Populations and Evolution · Quantitative Biology 2026-01-13 Luis F. Gordillo , Priscilla E. Greenwood

In this work, we consider, in a general setting, multiparameter multidimensional Markov processes that are time-changed by an independent additive subordinator. By extending Phillips theorem, we show that the resulting process is a Feller…

Probability · Mathematics 2026-03-12 Giuseppe D'Onofrio , Alessandro Mutti , Patrizia Semeraro

In this paper we study the L\'evy Ornstein- Uhlenbeck equation $\partial_t X_t=-m\,X_t+\eta$. The transition kernel of the L\'evy Ornstein- Uhlenbeck process is given by a series which is not convergent in general, a large diffusion…

Mathematical Physics · Physics 2011-04-11 Boubaker Smii

The quintic Ornstein-Uhlenbeck volatility model is a stochastic volatility model where the volatility process is a polynomial function of degree five of a single Ornstein-Uhlenbeck process with fast mean reversion and large vol-of-vol. The…

Mathematical Finance · Quantitative Finance 2023-05-10 Eduardo Abi Jaber , Camille Illand , Shaun , Li