scholarly journals A Large-Deviation Principle for Random Evolution Equations

Bernoulli ◽  
2000 ◽  
Vol 6 (6) ◽  
pp. 977 ◽  
Author(s):  
Mohamed Mellouk

Author(s):  
Hassan Dadashi

We demonstrate the large deviation principle in the small noise limit for the mild solution of semilinear stochastic evolution equations with monotone nonlinearity and multiplicative Poisson noise. A recently developed method in studying the large deviation principle, weak convergent method, is employed. We apply the result obtained by Budhiraja et al.,7 that reveals the variational representation of exponential integrals w.r.t. the Poisson random measure. Our framework covers a wide range of parabolic, hyperbolic and functional differential equations. We give some examples to illustrate the applications of our results.



2003 ◽  
Author(s):  
Paul Dupuis ◽  
Carl Nuzman ◽  
Phil Whiting


Author(s):  
Andrei Khrennikov ◽  
Achref Majid

In this paper, we prove a large deviation principle for the background field in prequantum statistical field model. We show a number of examples by choosing a specific random field in our model.



2010 ◽  
Vol 10 (03) ◽  
pp. 315-339 ◽  
Author(s):  
A. A. DOROGOVTSEV ◽  
O. V. OSTAPENKO

We establish the large deviation principle (LDP) for stochastic flows of interacting Brownian motions. In particular, we consider smoothly correlated flows, coalescing flows and Brownian motion stopped at a hitting moment.



Author(s):  
Paola Bermolen ◽  
Valeria Goicoechea ◽  
Matthieu Jonckheere ◽  
Ernesto Mordecki


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