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We present a comprehensive investigation of $\epsilon$-entropy, $h(\epsilon)$, in dynamical systems, stochastic processes and turbulence. Particular emphasis is devoted on a recently proposed approach to the calculation of the…

Chaotic Dynamics · Physics 2009-10-31 M. Abel , L. Biferale , M. Cencini , M. Falcioni , D. Vergni , A. Vulpiani

The combination of continuum Many-Body Quantum physics and Monte Carlo methods provide a powerful and well established approach to first principles calculations for large systems. Replacing the exact solution of the problem with a…

Computational Physics · Physics 2009-10-01 J. R. Trail

The main purpose of this paper is to study both the underdamped and the overdamped dynamics of the nonlinear Helmholtz oscillator with a fractional order damping. For that purpose, we use the Grunwald-Letnikov fractional derivative…

Adaptation and Self-Organizing Systems · Physics 2024-04-30 Adolfo Ortiz , Jianhua Yang , Mattia Coccolo , Jesús M. Seoane , Miguel A. F. Sanjuán

In this paper we consider the Allen-Cahn equation perturbed by a stochastic flux term and prove a large deviation principle. Using an associated stochastic flow of diffeomorphisms the equation can be transformed to a parabolic partial…

Probability · Mathematics 2015-01-19 Martin Heida , Matthias Röger

Effective harmonic methods allow for calculating temperature dependent phonon frequencies by incorporating the anharmonic contributions into an effective harmonic Hamiltonian. The systematic errors arising from such an approximation are…

Materials Science · Physics 2019-06-05 Erki Metsanurk , Mattias Klintenberg

We consider generalized Bayesian inference on stochastic processes and dynamical systems with potentially long-range dependency. Given a sequence of observations, a class of parametrized model processes with a prior distribution, and a loss…

Statistics Theory · Mathematics 2023-04-26 Langxuan Su , Sayan Mukherjee

Safety evaluation of self-driving technologies has been extensively studied. One recent approach uses Monte Carlo based evaluation to estimate the occurrence probabilities of safety-critical events as safety measures. These Monte Carlo…

Methodology · Statistics 2019-07-19 Zhiyuan Huang , Mansur Arief , Henry Lam , Ding Zhao

The problem of estimating the probability p=P(g(X<0) is considered when X represents a multivariate stochastic input of a monotone function g. First, a heuristic method to bound p is formally described, involving a specialized design of…

Statistics Theory · Mathematics 2015-03-17 Nicolas Bousquet

We prove a large deviations principle for the class of multidimensional affine stochastic volatility models considered in (Gourieroux, C. and Sufana, R., J. Bus. Econ. Stat., 28(3), 2010), where the volatility matrix is modelled by a…

Pricing of Securities · Quantitative Finance 2018-06-20 Aurélien Alfonsi , David Krief , Peter Tankov

We establish the large deviation principle for solutions of one-dimensional SDEs with discontinuous coefficients. The main statement is formulated in a form similar to the classical Wentzel--Freidlin theorem, but under the considerably…

Probability · Mathematics 2016-07-14 Alexei Kulik , Daryna Sobolieva

We utilize the weak convergence method to establish the Freidlin--Wentzell large deviations principle (LDP) for stochastic delay differential equations (SDDEs) with super-linearly growing coefficients, which covers a large class of cases…

Probability · Mathematics 2022-01-04 Diancong Jin , Ziheng Chen , Tau Zhou

In this paper, we aim to study the asymptotic behavior for multi-scale McKean-Vlasov stochastic dynamical systems. Firstly, we obtain a central limit type theorem, i.e, the deviation between the slow component $X^{\varepsilon}$ and the…

Probability · Mathematics 2023-06-02 Wei Hong , Shihu Li , Wei Liu , Xiaobin Sun

We give a probabilistic interpretation of the Monte Carlo scheme proposed by Fahim, Touzi and Warin [Ann. Appl. Probab. 21 (2011) 1322-1364] for fully nonlinear parabolic PDEs, and hence generalize it to the path-dependent (or…

Probability · Mathematics 2014-07-03 Xiaolu Tan

The efficiency of Hamiltonian Monte Carlo (HMC) can suffer when sampling a distribution with a wide range of length scales, because the small step sizes needed for stability in high-curvature regions are inefficient elsewhere. To address…

Machine Learning · Statistics 2023-11-09 Chirag Modi , Alex Barnett , Bob Carpenter

Quantum mechanics for many-body systems may be reduced to the evaluation of integrals in 3N dimensions using Monte-Carlo, providing the Quantum Monte Carlo ab initio methods. Here we limit ourselves to expectation values for trial…

Computational Physics · Physics 2010-11-22 John Robert Trail , Ryo Maezono

The safety concern for unmanned systems, namely the concern for the potential casualty caused by system abnormalities, has been a bottleneck for their development, especially in populated areas. Evidently, the collision between the unmanned…

Robotics · Computer Science 2020-03-10 Zhang Hepeng , Quan Quan

We consider the (barotropic) Euler system describing the motion of a compressible inviscid fluid driven by a stochastic forcing. Adapting the method of convex integration we show that the initial value problem is ill-posed in the class of…

Analysis of PDEs · Mathematics 2020-03-25 Dominic Breit , Eduard Feireisl , Martina Hofmanova

This article aims to derive a practical tracking control algorithm for flexible air-breathing hypersonic vehicles (FAHVs) with lumped disturbances, unmeasurable states and actuator failures. Based on the framework of the backstepping…

Systems and Control · Electrical Eng. & Systems 2025-04-15 Tianlong Zhao , Fei Hao

We consider the variational problem associated with the Freidlin--Wentzell Large Deviation Principle (LDP) for the Stochastic Heat Equation (SHE). For a general class of initial-terminal conditions, we show that a minimizer of this…

Probability · Mathematics 2024-05-17 Li-Cheng Tsai

This paper develops a multifidelity method that enables estimation of failure probabilities for expensive-to-evaluate models via information fusion and importance sampling. The presented general fusion method combines multiple probability…

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