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Author

Bagci, Hakan (34)

Ulku, Huseyin Arda (16)Desmal, Abdulla (8)Uysal, Ismail Enes (8)Sayed, Sadeed B (7)View MoreDepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division (33)Electrical Engineering Program (32)Physical Sciences and Engineering (PSE) Division (5)Applied Mathematics and Computational Science Program (3)Materials Science and Engineering Program (2)View MoreSubjectCEM (15)electromagnetic scattering (1)electromagnetics and photonics (1)MLMC (1)multi-level Monte Carlo (1)View MoreType
Poster (34)

Year (Issue Date)2019 (1)2016 (7)2015 (8)2014 (18)Item AvailabilityOpen Access (34)

Now showing items 1-10 of 34

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Computation of Electromagnetic Fields Scattered From Dielectric Objects of Uncertain Shapes Using MLMC Center for Uncertainty

Litvinenko, Alexander; Haji Ali, Abdul Lateef; Uysal, Ismail Enes; Ulku, Huseyin Arda; Oppelstrup, Jesper; Tempone, Raul; Bagci, Hakan (2015-01-05) [Poster]

Simulators capable of computing scattered fields from objects of uncertain shapes are highly useful in electromagnetics and photonics, where device designs are typically subject to fabrication tolerances. Knowledge of statistical variations in scattered fields is useful in ensuring error-free functioning of devices. Oftentimes such simulators use a Monte Carlo (MC) scheme to sample the random domain, where the variables parameterize the uncertainties in the geometry. At each sample, which corresponds to a realization of the geometry, a deterministic electromagnetic solver is executed to compute the scattered fields. However, to obtain accurate statistics of the scattered fields, the number of MC samples has to be large. This significantly increases the total execution time. In this work, to address this challenge, the Multilevel MC (MLMC) scheme is used together with a (deterministic) surface integral equation solver. The MLMC achieves a higher efficiency by “balancing” the statistical errors due to sampling of the random domain and the numerical errors due to discretization of the geometry at each of these samples. Error balancing results in a smaller number of samples requiring coarser discretizations. Consequently, total execution time is significantly shortened.

Computation of Electromagnetic Fields Scattered From Objects With Uncertain Shapes Using Multilevel Monte Carlo Method

Litvinenko, Alexander; Yucel, Abdulkadir; Bagci, Hakan; Oppelstrup, Jesper; Tempone, Raul; Michielssen, Eric (2019-02-14) [Poster]

Computational 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.

Transient Analysis of Electromagnetic Wave Interactions on Ferromagnetic Structures Using Landau-Lifshitz-Gilbert and Volume Integral Equations

Sayed, Sadeed B; Ulku, Huseyin Arda; Bagci, Hakan (2016-01-06) [Poster]

Analysis of Transient Electromagnetic Interactions on Nanodevices Using a Quantum-corrected Integral Equation Approach

Uysal, Ismail Enes; Ulku, Huseyin Arda; Bagci, Hakan (2016-01-06) [Poster]

A Sparsity-Regularized Reconstruction of Two-Dimensional Piecewise Continuous Domains!

Sandhu, Ali Imran; Desmal, Abdulla; Bagci, Hakan (2016-01-06) [Poster]

A Nonlinear Sparse Electromagnetic Imaging Scheme Accelerated with Projected Steepest Descent Algorithm

Desmal, Abdulla; Bagci, Hakan (2016-01-06) [Poster]

An Adaptive Hierarchical Sparse Grid Collocation Method for Stochastic Characterizaton of Electromagnetic/Circuit Systems

Li, Ping; Jiang, Lijun; Bagci, Hakan (2016-01-06) [Poster]

Computation of Electromagnetic Fields Scattered From Dielectric Objects of Uncertain Shapes Using MLMC

Litvinenko, Alexander; Haji Ali, Abdul Lateef; Uysal, Ismail Enes; Ulku, Huseyin Arda; Tempone, Raul; Bagci, Hakan; Oppelstrup, Jesper (2015-01-07) [Poster]

Simulators capable of computing scattered fields from objects of uncertain shapes are highly useful in electromagnetics and photonics, where device designs are typically subject to fabrication tolerances. Knowledge of statistical variations in scattered fields is useful in ensuring error-free functioning of devices. Oftentimes such simulators use a Monte Carlo (MC) scheme to sample the random domain, where the variables parameterize the uncertainties in the geometry. At each sample, which corresponds to a realization of the geometry, a deterministic electromagnetic solver is executed to compute the scattered fields. However, to obtain accurate statistics of the scattered fields, the number of MC samples has to be large.
This significantly increases the total execution time. In this work, to address this challenge, the Multilevel MC (MLMC [1]) scheme is used together with a (deterministic) surface integral equation solver. The MLMC achieves a higher efficiency by “balancing” the statistical errors due to sampling of the random domain and the numerical errors due to discretization of the geometry at each of these samples. Error balancing results in a smaller number of samples requiring coarser discretizations. Consequently, total execution time is significantly shortened.

Analysis of Transient Electromagnetic Wave Interactions on Graphene Sheets Using Integral Equations

Shi, Yifei; Sandhu, Ali Imran; Li, Peng; Uysal, Ismail Enes; Ulku, Huseyin Arda; Bagci, Hakan (2015-01-07) [Poster]

An Explicit and Stable MOT Solver for Time Domain Volume Electric Field Integral Equation

Sayed, Sadeed B; Ulku, Huseyin Arda; Bagci, Hakan (2014-05-04) [Poster]

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