What is it about?

We use Multi-Level Monte Carlo (MLMC) method to estimate propagation of uncertainties in electromagnetic wave scattering problems. The computational domain is a dielectric object with uncertain shape. MLMC uses a hierarchy of spatial meshes and optimally balances the statistical and discretisation errors.

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Why is it important?

NUMERICAL methods for predicting radar and scattering cross sections (RCS and SCS) of complex targets find engineering applications ranging from microwave remote sensing soil/ocean surface and vegetation to enhancing Raman spectroscopy using metallic nanoparticles. When the target size is comparable to or larger than the wavelength at the operation frequency, the scattered field is a strong function of the target shape. However, in many of the applications, whether the target is a (vegetated) rough surface or a nanoparticle, its exact shape may not be known and has to be parameterized using a stochastic/statistical model.


This is a very serious project. An international team of five professors and one research scientist were involved. The result of our 3 years work is - a computational framework for efficient and accurate characterizing EM wave scattering from dielectric objects with uncertain shapes. Our framework uses the Multi-Level Monte Carlo (MLMC) algorithm, which reduces the computational cost of the traditional MC method by performing most of the simulations with lower accuracy and lower cost (using coarser meshes) and smaller number of simulations with higher accuracy and higher cost (using finer meshes).

Dr. Alexander Litvinenko
Rheinisch Westfalische Technische Hochschule Aachen

Read the Original

This page is a summary of: MLMC method to estimate propagation of uncertainties in electromagnetic fields scattered from objects of uncertain shapes, PAMM, January 2021, Wiley,
DOI: 10.1002/pamm.202000064.
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