Stochastic differential equations for modeling of nonlinear wave-particle interaction

Author(s):  
Alexander Lukin ◽  
Anton Artemyev ◽  
Anatoly Petrukovich

<p>The charged particle resonant interaction with electromagnetic waves propagating in an inhomogeneous plasma determines the dynamics of plasma populations in various space plasma systems, such as shock waves, radiation belts, and plasma injection regions. For systems with small wave amplitudes and a broad wave spectrum, such resonant interaction is well described within a framework of the quasi-linear theory, which is based on the Fokker-Planck diffusion equation. However, in systems with intense waves, this approach is inapplicable, because nonlinear resonant effects (such as phase bunching and phase trapping) and non-diffusive processes play an essential role in the acceleration and scattering of charged particles. In this work we consider a generalized approach for modelling of wave-particle resonant interaction for intense coherent waves. This approach is based on application of stochastic differential equations for simulation resonant scattering and trapping. To test and verify an applicability of this approach, we use a simple model system with high-amplitude electrostatic whistler waves and energetic electrons propagating in the Earth radiation belts. We show that the proper determination of the model parameters allows us to describe the dynamics of the electron distribution function evolutions dominated by nonlinear resonant effects. Moreover, the proposed approach significantly reduces the calculation time in comparison with test particles methods generally used for simulations of nonlinear wave-particle interactions.</p>

2013 ◽  
Vol 7 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Adriano F. Siqueira ◽  
Oswaldo L. C. Guimaraes ◽  
Helcio J. Izario Filho ◽  
Domingos S. Giordani ◽  
Ivy dos Santos Oliveira ◽  
...  

Several papers in the literature on Advanced Oxidation Processes (AOPs) confirm the process as a viable alternative for the treatment of a variety of industrial effluents. In many of these works, modeling the variations of Chemical Oxygen Demand (COD) as a function of different experimental conditions was performed by techniques such as Design of Experiments, Artificial Neural Networks and Multivariate Analysis. These techniques require both a large number of parameters and a large quantity of experimental data for a systematic study of the model parameters as a function of experimental conditions. On the other hand, the study of Stochastic Differential Equations (SDE) is presently well developed with several practical applications noted in the literature. This paper presents a new approach in studying the variations of COD in AOPs via SDE. Specifically, two effluents, from the manufacture of paints and textiles were studied by combined treatment of the photo-Fenton process and catalytic ozonization.


Author(s):  
Andre Loerx ◽  
Ekkehard W. Sachs

We consider calibration problems for models of pricing derivatives which occur in mathematical finance. We discuss various approaches such as using stochastic differential equations or partial differential equations for the modeling process. We discuss the development in the past literature and give an outlook into modern approaches of modelling. Furthermore, we address important numerical issues in the valuation of options and likewise the calibration of these models. This leads to interesting problems in optimization, where, e.g., the use of adjoint equations or the choice of the parametrization for the model parameters play an important role. 


2012 ◽  
Author(s):  
Bo Jiang ◽  
Roger Brockett ◽  
Weibo Gong ◽  
Don Towsley

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