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: Efficient Hybrid Model of Field and Energy Flow in Interconnected Wave Chaotic Systems

ORAL

Abstract

Predicting energy flow through interconnected complex billiards is of keen interest to many fields. The Random Coupling Model (RCM) has been successfully applied to predicting the electromagnetic (EM) field statistical properties of various wave chaotic systems. Recent studies extend RCM to networks of coupled systems with multiple connecting channels [arXiv:1909.03827]. However the model becomes computationally costly as more billiards are added to the network. The Power Balance Model (PWB) can produce fast predictions for the averaged power density of waves in electrically-large systems. However the fluctuations of the wave field are lost in PWB, and many other mean-field approaches. Here we combine the best aspects of each model to create a hybrid treatment and study the EM fields in arrays of coupled complex systems. The proposed hybrid approach provides both mean and fluctuation information of the EM fields without the full computational demand of RCM. We compare the hybrid model predictions with experiments on linear cascades of overmoded cavities of various degrees of loss and find good agreement. The range of validity and applicability of the hybrid method is also discussed.

Presenters

  • Steven Anlage

    University of Maryland, College Park, Department of Physics and Department of Electrical and Computer Engineering, University of Maryland, College Park, Physics Department, University of Maryland, College Park, Center for Quantum Materials, University of Maryland

Authors

  • Steven Anlage

    University of Maryland, College Park, Department of Physics and Department of Electrical and Computer Engineering, University of Maryland, College Park, Physics Department, University of Maryland, College Park, Center for Quantum Materials, University of Maryland

  • Shukai Ma

    University of Maryland, College Park

  • Sendy Phang

    George Green Institute for Electromagnetics Research, University of Nottingham

  • Zachary Drikas

    US Naval Research Laboratory, Washington, DC

  • Bisrat Addisie

    US Naval Research Laboratory, Washington, DC

  • Ronald Hong

    US Naval Research Laboratory, Washington, DC

  • Valon Blakaj

    School of Mathematical Sciences, University of Nottingham

  • Gabriele Gradoni

    School of Mathematical Sciences, University of Nottingham

  • Gregor Tanner

    School of Mathematical Sciences, University of Nottingham

  • Thomas M Antonsen

    University of Maryland, College Park

  • Edward Ott

    University of Maryland, College Park