scholarly journals Large deviation principle of occupation measures for non-linear monotone SPDEs

Author(s):  
Ran Wang ◽  
Jie Xiong ◽  
Lihu Xu
2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Ran Wang ◽  
Jianliang Zhai ◽  
Shiling Zhang

<p style='text-indent:20px;'>In this paper, we establish a large deviation principle for stochastic Burgers type equation with reflection perturbed by the small multiplicative noise. The main difficulties come from the highly non-linear coefficient and the singularity caused by the reflection. Here, we adopt a new sufficient condition for the weak convergence criteria, which is proposed by Matoussi, Sabbagh and Zhang [<xref ref-type="bibr" rid="b14">14</xref>].</p>


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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