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dc.contributor.authorLitvinenko, Alexander
dc.contributor.authorYucel, Abdulkadir
dc.contributor.authorBagci, Hakan
dc.contributor.authorOppelstrup, Jesper
dc.contributor.authorTempone, Raul
dc.contributor.authorMichielssen, Eric
dc.date.accessioned2019-02-14T14:39:46Z
dc.date.available2019-02-14T14:39:46Z
dc.date.issued2019-02-14
dc.identifier.urihttp://hdl.handle.net/10754/631060
dc.description.abstractComputational tools for characterizing electromagnetic scattering from objects with uncertain shapes are needed in various applications ranging from remote sensing at microwave frequencies to Raman spectroscopy at optical frequencies. Often, such computational tools use the Monte Carlo (MC) method to sample a parametric space describing geometric uncertainties. For each sample, which corresponds to a realization of the geometry, a deterministic electromagnetic solver computes the scattered fields. However, for an accurate statistical characterization the number of MC samples has to be large. In this work, to address this challenge, the continuation multilevel Monte Carlo (CMLMC) method is used together with a surface integral equation solver. The CMLMC method optimally balances statistical errors due to sampling of the parametric space, and numerical errors due to the discretization of the geometry using a hierarchy of discretizations, from coarse to fine. The number of realizations of finer discretizations can be kept low, with most samples computed on coarser discretizations to minimize computational cost. Consequently, the total execution time is significantly reduced, in comparison to the standard MC scheme.
dc.description.sponsorshipKAUST
dc.relation.urlhttps://arxiv.org/pdf/1809.00362.pdf
dc.subjectuncertain geomentry
dc.subjectmulti-level Monte Carlo
dc.subjectMLMC
dc.subjectelectromagnetic scattering
dc.subjectradar cross section
dc.titleComputation of Electromagnetic Fields Scattered From Objects With Uncertain Shapes Using Multilevel Monte Carlo Method
dc.typePoster
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.conference.date26.03.2019
dc.conference.nameSIAM CSE 2019 Conference
dc.conference.locationSpokane, USA
dc.contributor.institutionRWTH Aachen
dc.contributor.institutionNanyang Technological University in Singapore
dc.contributor.institutionKTH Royal Institute of Technology
dc.contributor.institutionUniversity of Michigan
refterms.dateFOA2019-02-14T14:39:46Z


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