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Author

Bagci, Hakan (8)

Uysal, Ismail Enes (8)

Ulku, Huseyin Arda (7)Haji Ali, Abdul Lateef (2)Litvinenko, Alexander (2)View MoreDepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division (8)
Electrical Engineering Program (8)

Computer, Electrical and Mathematical Sciences & Engineering (CEMSE) (7)Physical Sciences and Engineering (PSE) Division (3)Applied Mathematics and Computational Science Program (2)View MoreJournal2018 International Applied Computational Electromagnetics Society Symposium (ACES) (1)PublisherIEEE (1)SubjectCEM (3)View MoreTypePoster (7)Conference Paper (1)Year (Issue Date)2018 (1)2016 (2)2015 (3)2014 (2)Item Availability
Open Access (8)

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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]

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; Oppelstrup, Jesper; Tempone, Raul; Bagci, Hakan (2016-01-06) [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.

A Novel Time Domain Method for Simulating Dissipative Electromagnetic Field Interactions

Uysal, Ismail Enes; Ulku, Huseyin Arda; Bagci, Hakan (2014-05-04) [Poster]

MOT Solution of Time Domain PMCHWT Integral Equation for Conductive Dielectric Scatterers

Uysal, Ismail Enes; Ulku, Huseyin Arda; Bagci, Hakan (2014-01-06) [Poster]

A Novel Time Domain Method for Characterizing Plasmonic Field Interactions

Uysal, Ismail Enes; Ulku, Huseyin Arda; Bagci, Hakan (2015-01-07) [Poster]

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]

A volume integral equation solver for quantum-corrected transient analysis of scattering from plasmonic nanostructures

Sayed, Sadeed Bin; Uysal, Ismail Enes; Bagci, Hakan; Ulku, H. Arda (2018 International Applied Computational Electromagnetics Society Symposium (ACES), IEEE, 2018-05-24) [Conference Paper]

Quantum tunneling is observed between two nanostructures that are separated by a sub-nanometer gap. Electrons “jumping” from one structure to another create an additional current path. An auxiliary tunnel is introduced between the two structures as a support for this so that a classical electromagnetic solver can account for the effects of quantum tunneling. The dispersive permittivity of the tunnel is represented by a Drude model, whose parameters are obtained from the electron tunneling probability. The transient scattering from the connected nanostructures (i.e., nanostructures plus auxiliary tunnel) is analyzed using a time domain volume integral equation solver. Numerical results demonstrating the effect of quantum tunneling on the scattered fields are provided.

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